JP6771968B2 - Information acquisition device, imaging device and information acquisition method - Google Patents

Description

The present invention relates to an information acquisition device, a photographing device, and an information acquisition method.

Examples of means capable of imaging a tissue structure or a vascular structure in a living body include magnetic resonance imaging (MRI) and X-ray CT (X-ray Computed Tomography). However, these methods have problems such as the use of a contrast medium and exposure to radiation, and a non-exposure non-invasive observation method is required.

Light measurement technology is an example of a non-exposure / non-invasive measurement method. However, the living body is a strong scattering body with respect to light, and in the observation of the tissue in the living body by light, the tissue structure is blurred and the image contrast is lowered due to the influence of the scattered light. Therefore, when observing a blood vessel such as a small blood vessel in which contrast is likely to decrease due to scattering or a new blood vessel group having weak light absorption and low contrast, it is required to extract and emphasize the blood vessel image.

By the way, Patent Document 1 discloses that in the field of vein recognition, a venous vascular pattern is extracted by using a filter that reduces low frequency components and high frequency components lower than the spatial frequency of veins.

International Publication No. 2013/0885666

However, there is a high possibility that the spatial frequency of the image of the new blood vessel group is low, and when the method of Patent Document 1 is used, it becomes difficult to extract the pattern of the new blood vessel group. Therefore, it is required to accurately acquire information on blood vessels regardless of the spatial frequency of the blood vessel image. An object of the present invention is to provide an information acquisition device, an imaging device, and an information acquisition method capable of accurately acquiring information on blood vessels.

The information acquisition device according to one aspect of the present invention acquires a blood vessel image of a blood vessel included in the imaging site by combining with a blood flow changing portion that is arranged outside the imaging site and changes the blood flow of the imaging site. The first part of the information acquisition device for acquiring a plurality of image data including the imaging site in the imaging region corresponding to a plurality of imaging times in which the operating state of the blood vessel changing portion is different, and the blood vessel change. second part for generating a difference of image data difference processing selected from a selected plurality of image data between different image data to include image data obtained in response to shooting time immediately after the operation of the parts In the difference image data and the plurality of image data, a first region that is a part of a region corresponding to a blood vessel and a part of a region adjacent to the first region and other than a region corresponding to the blood vessel. Contrast is emphasized from the third part of acquiring index data using the data in the second region, and the image data group including the difference image data and the plurality of image data based on the index data. and a fourth portion for selecting the relevant information of the image data including image data or blood vessel image in which the contrast is emphasized including the blood vessel image that is characterized by that having a.
Further, the method of acquiring information on one aspect according to the present invention includes a step of attaching a blood flow changing portion for changing the blood flow of the imaging site to a subject including the imaging site, and a method of attaching a blood vessel included in the imaging site. Corresponding to the first step of acquiring a plurality of image data including the imaging site in the imaging region by photographing at a plurality of times so that the blood flow is different, and the imaging time immediately after the operation of the blood flow changing portion. The second step of generating the difference image data that has been subjected to the difference processing between the different image data selected from the plurality of image data selected so as to include the acquired image data, the difference image data, and the plurality of image data. In, using the data in the first region which is a part of the region corresponding to the blood vessel and the second region which is adjacent to the first region and is a part of the region other than the region corresponding to the blood vessel. From the third step of acquiring the index data and the image data group including the difference image data and the plurality of image data based on the index data, the image data including the blood vessel image with enhanced contrast or the contrast is obtained. It is characterized by having a fourth step of selecting relevant information of image data including an enhanced vascular image.

According to the present invention, it is possible to accurately acquire information on blood vessels.

The figure which shows the captured image explaining the 1st region and the 2nd region. The figure explaining the index value and the blood vessel image intensity of the 1st region and the 2nd region in an image. The figure explaining the index value and the blood vessel image intensity of the 1st region and the 2nd region in an image. The figure which shows the captured image explaining the 1st region and the 2nd region Schematic diagram showing the information acquisition device of the first embodiment The figure which shows the relationship between the applied pressure and time from the start of shooting to the end of shooting. The figure explaining the index value and the blood vessel image intensity of the 1st region and the 2nd region of the difference image. The figure explaining an example of the flowchart which generates a blood vessel image A diagram illustrating another example of a flowchart that generates a blood vessel image. A diagram illustrating yet another example of a flowchart that generates a blood vessel image. The figure which shows the example of the light source applicable to this invention. The figure which shows the relationship of the lighting wavelength of a light source with respect to time

In the information acquisition method of one aspect of the present invention, a plurality of image data including an imaging site including a blood vessel are acquired under different imaging conditions (first step), and difference processing is performed between different image data selected from the plurality of image data. The difference image data which is the obtained data is generated (second step). Then, in each of the plurality of image data including the difference image data, the index data is acquired (third step), and based on the index data, the image data or the image is obtained from the plurality of image data including the difference image data. Select the relevant information for the data (4th step). In the second step, the difference processing is performed between the different image data including the image data selected based on the blood flow fluctuation information in one region of the imaging site. In addition, the third step includes a first region that is a part of the region corresponding to the blood vessel and a second region that is adjacent to the first region and is a part of the region other than the region corresponding to the blood vessel. The index data is acquired using the data in.

For example, one region of the imaging region is at least one of the first region and the second region, and a plurality of pairs of the first region and the second region are set. There are various modes of each step as described in the embodiments and examples described later. The information acquisition device of another aspect of the present invention has first to fourth parts for executing the functions of the first to fourth steps, respectively.

Hereinafter, embodiments and examples of the present invention will be described, but they do not limit the present invention in any way. The imaging device according to the embodiment of the present invention includes at least a light source, a detection unit, and an information acquisition device including a processing unit (the first to fourth parts). Light from a light source is applied to, for example, a part of the subject's body (subject), at least one of transmitted light, reflected light, and scattered light is detected by a detection unit, and a plurality of images of the imaged part are photographed differently. Obtained under conditions. In the imaging device of the present embodiment, a plurality of such images obtained by photographing a blood vessel of interest under different conditions are used, processed by a processing unit, and a blood vessel image or its related information is extracted by difference processing between the plurality of images. For example, even in an image in which a faint blood vessel image (absorption image) exists in the background distribution due to scattered light in normal transmission photography, the scattered light component or the like is removed from the image by the difference processing between the plurality of image data. Blood vessel images can be extracted.

(Explanation of the process of acquiring a plurality of image data (original images) including an imaging site including a blood vessel under different imaging conditions)
First, the difference in the blood vessel image due to the difference in the imaging conditions recorded by the apparatus of the present embodiment will be described. Differences in blood vessel images include, for example, changes in transmittance of blood vessels due to changes in blood flow, changes in light absorption, and the like. Causes or methods that cause fluctuations in blood flow include the following. For example, there are constant blood flow fluctuations in the human body caused by the beating of the heart. Further, even if the positional relationship between the height of the part to be imaged and the height of the subject's heart is changed, blood flow fluctuation can occur. Alternatively, using a blood flow changing part (cuff) that changes the blood flow of the blood vessel from the outside, the pressure that presses the part closer to the heart than the imaged part is changed to change the blood flow of the imaged part. It may be varied.

The blood vessels normally present in the human body are roughly divided into arteries, capillaries, and veins. Arteries are classified into aorta, arteries, and arterioles. The inner diameter of the aorta is approximately 2.5 cm, the artery is 0.4 cm, and the arteriole is 30 μm. The inner diameter of the capillaries is 5 μm. Veins are classified into vena cava, vein, and venule. The inner diameter of the vena cava is 3 cm, the inner diameter of the vein is 0.5 cm, and the inner diameter of the venule is 20 μm.

Generally, the liquid flowing through the tube suffers pressure loss. Therefore, the pressure of the liquid that has been applied to a certain pressure and has flowed into the pipe decreases as the diameter of the pipe becomes smaller and the distance propagated in the pipe becomes longer. Therefore, even in the case of blood vessels, it is considered that the pressure from the heart and its fluctuation are more easily transmitted to thicker blood vessels and less likely to be transmitted to thinner blood vessels. In other words, it is considered that pressure loss is small in large blood vessels such as arteries and veins, blood pressure from the heart and its fluctuations are easily transmitted, and changes in blood flow due to blood pressure fluctuations are also large. On the other hand, in very thin blood vessels such as capillaries, blood pressure and its fluctuations are difficult to be transmitted, and changes in blood flow due to blood pressure fluctuations are considered to be small. Moreover, when not only the thickness of the blood vessel but also the structure of the blood vessel is different, it is considered that the difference in the elasticity of the blood vessel wall also affects the blood pressure and the easiness of transmitting the fluctuation. Therefore, it is considered that the change in light absorption of blood vessels due to fluctuations in blood pressure also differs depending on the type and thickness of blood vessels.

In addition, although it is not a blood vessel that is always present in the human body, there is a new blood vessel as a blood vessel newly generated in a diseased area or the like. Although each new blood vessel is a thin blood vessel, they are densely formed to form a dense new blood vessel group. In addition, as the condition progresses, the size of the new blood vessel group as a mass may increase, or the thickness of each new blood vessel constituting the new blood vessel group may increase. In a tissue in which a new blood vessel group is newly generated, a new blood vessel group is formed in addition to the originally existing capillaries and other blood vessels, so that it is considered that the volume occupancy of blood vessels and blood increases. Therefore, it is considered that the fluctuation of light absorption by blood and the fluctuation of light absorption due to the fluctuation of blood flow rate are also larger than those of the tissue in which the neovascular group does not exist.

The present embodiment relates to an apparatus and a method for clearly extracting an image of a blood vessel as described above. A device or method specifically intended to image at least one of arteries, veins, and neovascularization groups.

As an example, when photographing a blood vessel near a joint, such as when photographing a new blood vessel group associated with rheumatoid arthritis, the imaging area is set to include the joint portion and an artery or vein. When the target is a new blood vessel group, it is preferable to set the new blood vessel group to be included, but the new blood vessel group may be difficult to see and its position may be difficult to understand from a simple transmission image or the like. In this case, as will be described later, first, an operation of extracting arteries and veins is performed. This operation makes it easier to see the new blood vessel group, and when the location can be specified, it is possible to extract the new blood vessel group more clearly by performing an arithmetic process that makes the new blood vessel group easier to see.

There are the following methods for acquiring blood vessel images with different imaging conditions. For example, it is possible to take a plurality of pictures at different shooting times. When a moving image is shot, each frame of the moving image becomes an image having a different shooting time. In this case, it is possible to record the time change of the blood vessel image, for example, when the blood flow rate and the intensity of light absorption by the blood vessel accompanying the change with time, the change can be recorded.

(Explanation of the process of acquiring index data or evaluation value in multiple image data)
Next, images taken under different shooting conditions and evaluation of index data or evaluation values in the images will be described by taking transmission shooting as an example. The evaluation of the index data or the evaluation value in the image can also be applied to the difference image data described later. Since blood vessels absorb light, they appear dark in normal transmission photography. Even in reflection photography, blood vessels absorb light and appear dark. Tissues such as fat, bone, and muscle scatter light strongly, so when a transmission image is taken of an artery or vein under the skin in a living body, the artery or vein image becomes a dark rod-shaped and blurred image. Fat and muscle, which are not blood vessels, absorb less light than blood vessels and appear brighter than blood vessels due to scattered light in the body. As a method of displaying an image, it is also possible to invert the light and darkness to brighten the portion where light absorption by blood vessels occurs and darken the portion where there is no absorption.

The evaluation of the intensity of the blood vessel image will be described. In the present embodiment, the intensity of the blood vessel image is evaluated by the difference in signal value between the darkest part at the substantially center of the blood vessel image and the bright part near the blood vessel. The portion where the amount of transmitted light is large is a portion where arteries or veins do not exist in a shallow portion under the skin and fat, muscle, etc. exist. In the present specification, this region is referred to as a fat portion (including a second region other than the first region). On the other hand, the blood vessel portion (including the first region) absorbs light strongly by the blood vessel, so that the amount of transmitted light is smaller than that of the fat portion. Therefore, basically, the region on the side of the blood vessel portion having the largest pixel value (index value) is regarded as the fat portion. When there are multiple blood vessels in the vicinity, the position of the fat part is the position where the pixel value of the fat part is evaluated at the point between one blood vessel and another blood vessel closest to the blood vessel and having the largest amount of transmitted light. It is better to consider it as.

FIG. 1 is a schematic view of an example of a blood vessel image. The imaging region 101 includes a joint 102, a joint 103, a blood vessel 104, a blood vessel 107, and a blood vessel 109. FIG. 2 shows the distribution of the brightness of the image on the line segment connecting the points A 105 and 106 in FIG. At this time, the brightness of the image is evaluated for the blood vessel image 201 of FIG. 2, the center 202 of the blood vessel 104 of interest, the center 210 of the blood vessel 109, the fat portion 203, and the fat portion 204. Further, 205 indicates the position of point A in FIG. 1, and 206 indicates the position of point B in FIG. The position in FIG. 1 corresponding to the center 202 of the blood vessel image is the point 107, and the position corresponding to the fat portion 203 is the point 108 where the pixel value is the brightest. Then, the pixel corresponding to the point 107 is designated as the blood vessel pixel, and the pixel corresponding to the point 108 is designated as the fat pixel. From these regions, the pixel values of each region are obtained. Then, the brightness 207 of the fat portion beside the blood vessel image in FIG. 2 is defined as the pixel value of the fat pixel, the brightness 208 of the blood vessel image is defined as the pixel value of the blood vessel pixel, and the difference 209 is evaluated as the intensity of the blood vessel image. To do. This can be index data.

In the present embodiment, an example in which the position of the blood vessel pixel for evaluating the pixel value of the blood vessel image and the position of the fat pixel for evaluating the pixel value of the fat portion are separated in a direction substantially orthogonal to the traveling direction of the blood vessel. Shown. However, the method for evaluating the blood vessel image is not limited to this, and may deviate from the orthogonal direction. Further, it is preferable to set the blood vessel pixel for evaluating the blood vessel image and the fat pixel for evaluating the fat portion at positions that are not significantly separated from each other. For example, another blood vessel is set so as not to be inserted between the blood vessel pixel for evaluating the pixel value of the blood vessel and the fat pixel for evaluating the pixel value of the fat portion. As a result, the difference in pixel value between the blood vessel image and the closest fat portion thereof can be evaluated, so that the background light intensity distribution due to scattering is not easily affected, and the blood vessel image intensity can be easily evaluated accurately. This is because when the blood vessel pixel and the fat pixel are close to each other, if the blood vessel of the blood vessel pixel does not exist, it is highly likely that the pixel value of the blood vessel pixel and the pixel value of the fat pixel are close to each other. is there. The living body is a strong scatterer, and if the blood vessel pixels and the fat pixels are sufficiently close to each other, it is considered that the intensity distribution of the light transmitted through the living body is almost eliminated by scattering. Therefore, it can be considered that the difference in the pixel values between the blood vessel pixel and the fat pixel basically shows only the influence of the presence or absence of the blood vessel, and the difference in the pixel value between the blood vessel pixel and the fat pixel is considered to be the blood vessel image intensity. It will be good.

However, as the blood vessel pixel and the fat pixel are separated from each other, the intensity of the light transmitted through the living body is likely to be different between the blood vessel pixel and the fat pixel regardless of the presence or absence of the blood vessel. In this case, the blood vessel image intensity in the blood vessel pixel deviates from the difference between the pixel value of the blood vessel pixel and the pixel value of the fat pixel, and it becomes difficult to evaluate the blood vessel image intensity in the blood vessel pixel.

Therefore, it is preferable that the blood vessel pixel and the fat pixel are not largely separated from each other, and are separated from each other by the width of the blood vessel image as close as possible. From the above, the position where the fat pixel is set is on a straight line extending in a direction substantially orthogonal to the traveling direction of the blood vessel in which the blood vessel pixel is arranged through the blood vessel pixel, and the blood vessel in which the blood vessel pixel is arranged and its It is preferable to set the position between the adjacent blood vessels so that the pixel value takes the maximum value. This corresponds to setting the fat pixel at a position where the pixel value takes the minimum value because the blood vessel portion is bright and the fat portion is dark in the light-dark inverted image.

In addition, light scattering should be calculated in advance based on the typical value of the scattering coefficient of human tissue by numerical calculation, etc., and it is estimated how blurry a transmitted image shows a blood vessel image of a certain thickness and a certain depth. Is also suitable. For example, in the blurring of a blood vessel image at a depth of 1 mm, point source light is incident from one surface of a light scatterer corresponding to a human body tissue such as a fat part having a thickness of 1 mm as a parallel luminous flux and emitted from the other surface. It can be calculated from the half width of the spatial spread of the light intensity distribution (spread of the point image function). Then, the pixel value of the portion separated from the center of the blood vessel image rather than the blur of the blood vessel image estimated in this way may be regarded as the pixel value of the fat portion. For example, if the half-value half width of the blur of the blood vessel image is calculated to be 2 mm, the fat pixel is set by assuming that the point 2 mm or more away from the center of the blood vessel image is the pixel at the position of the fat portion. It is possible to evaluate the intensity of the blood vessel image from the pixel value of the fat portion estimated in this way and the pixel value of the center of the blood vessel image.

When a graph corresponding to FIG. 2 is created from an actual photographed image, noise is superimposed on the graph, and the position where the pixel value is maximum, that is, the position of the fat portion may be difficult to understand. Noise is often a component with a high spatial frequency. In that case, for example, noise is removed from the original image data as shown in FIG. 1 that generates the graph of FIG. 2 or the graph of FIG. 2, the position where the pixel value is maximum is found, and the fat pixel is placed at that position. It is preferable to set and evaluate. As the noise suppression processing, for example, a low-pass filter, various other filters, and a moving average processing can be performed. However, care must be taken not to attenuate the signal of the spatial frequency component corresponding to the size of the healthy blood vessel or the new blood vessel group, which is the observation target in the captured image. Alternatively, the noise width of the graph of FIG. 2 is evaluated separately, and the fat portion is selected from any pixel having a pixel value of L ± N obtained by adding the noise width N to the maximum pixel value L between the blood vessel images. It is also possible to select the position of.

Here, the contrast evaluation of the blood vessel image in the photographed image will be described. If the region of interest (ROI: Region of Interest) is set so that the blood vessel image is included in the imaging area and the minimum pixel value in the ROI is obtained, the contrast of the blood vessel image in the ROI can be calculated. Is. The contrast evaluation formula is, for example, the following (Equation 1).
(Ib-If) / (Ib + If) (Equation 1)

Ib in (Equation 1) is basically the pixel value of the blood vessel image, and If is the pixel value of the fat portion beside the blood vessel image, and is used as the pixel value of the pixel set as the blood vessel pixel and the fat pixel, respectively, as described above. get. When the blood vessel image is bright and the fat part is dark, the contrast is defined as a positive value, and vice versa. However, in the contrast evaluation of this case, the pixel value itself is not simply used, but the pixel value of the pixel that takes the minimum value in the ROI is acquired and then calculated as the difference from the pixel value. As shown in FIG. 2, If corresponds to 207, Ib corresponds to 208, and the position where the brightness = 0 of the image of the graph corresponds to the pixel position of the minimum pixel value in the ROI. In image display, a high-contrast blood vessel image can be displayed by displaying the minimum value in the ROI as a pixel value of 0, which is preferable. The contrast evaluation of the blood vessel image described above can be defined in the angiographic image itself, and can also be evaluated in the blood vessel image generated by the difference processing described later. Depending on how the blood vessel image is evaluated, different contrast definition formulas may be used as appropriate. Further, in order to simplify the processing, it is possible to perform the contrast evaluation processing by setting the minimum value of the entire image to 0 without setting the ROI as described above. According to the present invention, since batch image processing in a relatively wide area is possible, it is not always necessary to perform image processing such as setting a plurality of such ROIs and connecting them.

Regarding the evaluation of the intensity and contrast of the blood vessel image described above, the brightness of the fat parts on both sides of the blood vessel image may differ depending on the arrangement of the blood vessels of the subject and the imaging site. For example, the distribution of pixel values of an image including a blood vessel image is as shown in FIG. In this case, the intensity of the blood vessel image 301 is selected from, for example, the fat portion 302 and the fat portion 303 on both sides of the blood vessel image, whichever has the larger or smaller pixel value, and the pixel value 304 of the center 307 of the blood vessel image. It may be the difference in brightness of. Alternatively, the pixel value at the position where the blood vessel image is internally divided by the ratio of the pixel values of the fat portions on both sides of the blood vessel image may be 305, and the height difference between this and the pixel value at the center of the blood vessel image may be 306. When evaluating the intensity and contrast of a plurality of blood vessel images, it is preferable that the method of calculating the intensity of the blood vessel image is uniformly applied to the plurality of blood vessel images.

Further, depending on the subject and the imaging site, the position of the pixel value valley (when the light and dark are inverted) corresponding to the fat parts on both sides of the blood vessel image may be unclear. In that case, light scattering is calculated based on the typical value of the scattering coefficient of human tissue by numerical calculation in advance in the same manner as described above, and a transmitted image in which a blood vessel image of a certain thickness and a certain depth is blurred is obtained. It is also preferable to estimate whether it is shown.

Further, in the present embodiment, the number of pixels for evaluating the pixel value of the blood vessel image or the fat portion is described as one, but the present invention is not limited to this. For example, it is possible to set a blood vessel or a fat portion as a region in which a blood vessel pixel or a fat pixel is formed by a plurality of pixels, and to use the average of the pixel values of the plurality of pixels in the region as a pixel value of the blood vessel or the fat portion. By averaging, it is possible to mitigate the influence of noise in the image, which is preferable. Alternatively, it is also possible to evaluate by adopting the maximum value or the minimum value in the area.

(Explanation of the process of generating difference image data, which is data obtained by difference processing between different image data from a plurality of image data)
Next, the difference processing of the blood vessel image will be described. In the present embodiment, it is aimed to enhance the blood vessel image and increase the contrast by the difference processing between a plurality of original images having different imaging conditions of the blood vessel image. Images with different imaging conditions can be generated, for example, by photographing blood vessels a plurality of times at different times, as described above. In addition, high-speed continuous imaging such as photographing the same blood vessel as a moving image for a certain period of time is also suitable.

First, it is preferable to perform the alignment processing of the blood vessel images between the captured original images before the difference processing between the original images. This is because the imaging part of the subject may move during the imaging time. Even if the imaged part of the subject is held on the sample table, breathing, other movements, or involuntary movements may occur. For example, when a plurality of images are taken at intervals, the larger the time interval, the higher the possibility that the imaged portion moves with respect to the camera, and it is necessary to align the blood vessel image for each image.

The method of aligning the blood vessel images in the plurality of images is not particularly limited. For example, blood vessels themselves, fingerprints, wrinkles, scratches, etc. are used as feature points in the image, and one or more of these feature points are used for translation, rotation, magnification adjustment, etc. between images for alignment. It is possible. Further, the feature points are not limited to the feature points originally provided in the subject as described above, and it is also preferable to add a marker to a part of the imaging part of the subject before imaging. Assuming image alignment by affine transformation or the like, it is preferable to assign a plurality of markers. It is preferable that there are three or more points and at least three points are not in a straight line.

The difference processing between the original images will be described. For example, when there are two blood vessel images as original images and the difference processing is performed between them, the difference between the images can be processed by multiplying one image by a coefficient k. When three or more blood vessel images are taken, the combination of two image data selected based on the blood flow fluctuation information of at least one of the first region and the second region, the coefficient k of the above difference processing, and subtraction. Generate multiple difference images according to the order. The drawing order is whether to generate a difference image with image Ak × image B or to generate a difference image with image Bk × image A. Setting the coefficient to 1 is preferable because it simplifies the arithmetic processing and enables high-speed processing. It is also possible to set the coefficient to a value other than 1. In addition, the blood vessel image contrast of the difference image is calculated based on the blood vessel pixel value and the fat pixel value in the ROI set for the difference image or the difference image, and the minimum pixel value, and a coefficient that maximizes this value. You may find the value of. The plurality of difference images created in the above step may be continuously retained by the processing unit. Alternatively, only the data set (related information) related to the image data, such as the set of the original images A and B that created the difference image, the drawing order, and the value of the difference processing magnification, is retained and is required in other processes. Depending on the situation, the difference image may be generated again.

Further, the difference processing is not limited to the processing performed for each image. For example, in order to suppress random noise contained in the image, an image A obtained by averaging 10 images in which blood vessel images are aligned is prepared, and another image B obtained by averaging 10 images is also prepared. prepare. Then, it is also preferable to perform the difference processing between the image A and the image B, which are the processed image data. The average number of processed images is not limited to 10. In order to increase the noise reduction effect, it may be necessary to increase the number of integrated images. Random noise is suppressed in approximately proportion to the square root of the total number of images. Therefore, for example, in order to suppress noise to 1/10, it is necessary to generate an average image of 100 images. If the noise is random noise such as shot noise, it is also preferable to set the number of averaging processes for both of the original images to be differentiated to be equal. It is also preferable to use the original images whose shooting times are closest to each other in the averaging process. Alternatively, in the case of the original image generated by continuous shooting, it is also preferable to generate a plurality of images obtained by averaging the continuous images.

When a blood vessel image is extracted by performing a difference process between a plurality of images subjected to the above-mentioned averaging process, the same original image is not included in the averaged images used for the difference process (having common image data). Not) is preferable. That is, for example, the difference processing between the image A averaged by the original images 1, 2 and 3 and the original image B averaged by the original images 4, 5 and 6 is preferable. When the image C is generated by the averaging process of the original images 2, 3 and 4, the difference process between the image A and the image C and the difference process between the image B and the image C are also possible, but the former (same as above). Difference processing that does not include the original image) is preferable.

In the following, each process will be described by taking as an example the case where a plurality of images are captured by moving images. When moving image is taken, since the shooting time is different for each frame, the contrast and intensity of the image of the same blood vessel may be different between different frames, reflecting the fluctuation of the state of the human body. As described above, this can occur due to various causes such as the subject's pulsation, respiration, and posture change. It is preferable to wear a tourniquet (cuff) or the like to artificially cause blood flow fluctuation from the outside. Then, by selecting two blood vessel images having different blood vessel image intensities and performing the difference processing, it is possible to extract a high-contrast blood vessel image or extract a time change of the blood vessel image intensity. As described above, the two blood vessel images include image data selected based on the blood flow fluctuation information.

The selection of the image having the highest blood vessel image contrast among the images after the difference processing in the case of generating an image by the difference processing between a plurality of original images will be described. In addition, a method of selecting a plurality of original image sets and a difference processing magnification that maximizes the blood vessel image contrast of the image after the difference processing will be described. Here, it will be described as assuming that a region including joints and arteries (or veins or new blood vessel groups) is set as ROI in the imaging region.

For example, as shown in FIG. 4, a blood vessel for evaluating the blood vessel image intensity by including at least one of a joint 405 and a joint 406 in the ROI for a plurality of original images and a difference image generated by the difference processing between them. Specify at least one 404. Then, the blood vessel pixel located on the blood vessel and the fat pixel in the vicinity of the blood vessel pixel and separated from the blood vessel are set, and the pixel value in this region is acquired. In the example of FIG. 4, the blood vessel pixel 401, the fat pixel 402, and the ROI 403 are shown, respectively. Of the plurality of different images, the two images used to generate the difference image are referred to as a first image and a second image here. They perform the above-mentioned averaging process for each set consisting of two images selected based on blood flow fluctuation information from a plurality of frames shot in a moving image or a plurality of frames selected based on blood flow fluctuation information. It shall refer to the two images generated by applying the above.

When the blood flow of the human body fluctuates, the light absorption of the blood vessel portion fluctuates. For example, when a blood vessel in the upper arm is pressed with an instrument such as the cuff described above, the blood flow changes especially in the hand or finger on the side farther from the heart than the cuff. Therefore, in order to extract the blood flow change in the blood vessel portion, the pixel values of the blood vessel pixels may be compared between the images taken at different times. Images at different times can be acquired even by continuous photography, and can be acquired as images of each frame by taking a moving image. For example, by selecting two images with the largest pixel values of blood vessel images (these blood vessel images are selected based on blood flow fluctuation information) and performing difference processing on these two images, the blood vessels after the difference processing are performed. The intensity of the image can be maximized. In addition, basically, the pixel value of the fat pixel corresponding to the fat part is cut off as much as possible, and the difference processing is performed by selecting the original image set and the difference processing magnification k described later so that the blood vessel image intensity becomes as large as possible. The contrast of the later blood vessel image can be increased. At this time, it is preferable to increase the contrast of the blood vessel image that the pixel value of the fat pixel of the image after the difference processing is not significantly different from the minimum pixel value in the ROI of the image after the difference processing.

However, the present inventor has found that fluctuations in pixel values due to fluctuations in blood flow can occur not only in the blood vessel portion but also in the fat portion. It was also found that the change in the pixel value of the fat part also differs from place to place. It is considered that this is because very fine capillaries are also present in the fat part, and as a result, a small amount of blood and blood flow are present.

The change in the pixel value of the fat part strongly affects the contrast of the blood vessel image. Here, even in an image that has been subjected to processing such as light-dark inversion of the transmitted image, or a difference image by selecting an appropriate set of original images and a difference processing magnification, an image in which the blood vessel image becomes bright and the fat part becomes dark is obtained. It can be generated. In such an image, the minimum pixel value is often in the fat part. By allocating the pixel value distribution in the image or ROI to full scale and displaying it, the blood vessel image in the image or ROI can be displayed with high contrast and in an easy-to-see manner. Therefore, the blood vessel image contrast value in this display is the difference between the pixel value of the blood vessel pixel (blood vessel portion) and the minimum pixel value, and the pixel value and the minimum pixel of the fat pixel (fat portion) set in the vicinity of the blood vessel. Determined by the difference from the value. Therefore, since the minimum pixel value in the image or ROI affects the blood vessel image contrast, the original image and the difference processing thereof are taken into consideration in consideration of the pixel value of the fat portion and the minimum pixel value depending on the time change thereof. It is important to evaluate the contrast of the difference image generated in.

For example, in the difference image, when the pixel value of the blood vessel pixel and the pixel value of the fat pixel are calculated as the pixel value itself in the difference image without considering the minimum pixel value, the contrast value of (Equation 1) can be calculated. However, there is a possibility that the minimum pixel value is a negative value. Here, in a normal image display, when the pixel value is a negative value, the pixel value = 0, that is, it is displayed as pitch black, so that nothing is displayed on the image. That is, the image information is lost. Even if the pixel values of the blood vessel pixel and the fat pixel are positive values, it is not preferable that there is a negative pixel value. In order to avoid such loss of information, a certain value is added to all the pixels in the image or ROI so that the minimum pixel value becomes 0 so that all the pixel values become 0 or more. Display. For example, when the minimum pixel value is set to 0, the contrast value is different from the blood vessel image contrast when the minimum pixel value is not taken into consideration as described above, but the maximum contrast value can be achieved while avoiding information loss. Therefore, in the difference image or the original captured image, it is necessary to use the contrast value when the minimum pixel value in the image or the ROI is set to 0 for the blood vessel image contrast evaluation. It is difficult to estimate the minimum pixel value because the pixel value of the fat portion changes with time and the changes are scattered, and it is necessary to grasp each of the generated difference images one by one.

As described above, the human body has aorta, arteries, arterioles, vena cava, veins, venules, and capillaries. As described above, since the pixel value changes also in the fat part, it is considered that blood flow by capillaries exists even if veins and arteries are not visible in the fat part. Therefore, it is considered that blood flow fluctuations in capillaries can occur in the fat part as well as blood flow fluctuations in arteries and veins. In addition, since the thickness of capillaries is much smaller than that of veins and veins, it is considered that the pressure loss is large when the blood vessels are regarded as flow paths. Therefore, it is considered that the smaller the blood vessel, the smaller the fluctuation of blood flow caused by the fluctuation of blood pressure due to the internal factor such as pulsation and the external factor due to the use of the tourniquet. As a result, it is considered that the change in the pixel value due to the fluctuation of blood flow differs greatly between the fat part and the artery or vein. Alternatively, since the magnitude of resistance received by a fluid such as blood differs between a large blood vessel and a thin blood vessel, the relationship between blood flow and time when blood flow fluctuation occurs may also depend on the thickness of the blood vessel. For example, by extracting the difference in temporal variation characteristics depending on the thickness of blood vessels, it is possible to extract blood vessels separately for each thickness.

Here, based on the above points, an example of image generation by difference processing, blood vessel image contrast, and selection of a difference image based on the image contrast will be collectively described with reference to FIG. 7. The pixel value of the vascular pixel of the first image is α1, the pixel value of the vascular pixel of the second image is α2, the pixel value of the fat pixel of the first image is β1, and the pixel value of the fat pixel of the second image is β1. Let it be β2. Then, the lowest pixel value of the first image is d1 (not shown), and the lowest pixel value of the second image is d2 (not shown). It is assumed that both the first image and the second image (two blood vessel images are selected based on blood flow fluctuation information) are images in which the blood vessel image is bright and the fat portion is dark. Such an image in which the blood vessels are bright and the fat portion is dark can be generated by subjecting a normal transmission imaging result to light-dark inversion processing. As a result of evaluating the contrast of the blood vessel image as described above, if the contrast value is negative in the first image or the second image, it is recognized that the blood vessel image is dark and the fat part is bright. Then, the image may be inverted. The light-dark inversion process is a process in which each pixel value in an image is inverted with respect to half the value of the full scale.

In the following, the difference image and the first image and the second image that generate the difference image will be described in a unified manner as an image in which the blood vessel image is bright and the fat part is dark (contrast takes a positive value). ..

The difference image 703 is generated by the difference processing between the first image 701 and the second image 702. These relationships are shown in FIG. The contrast of the blood vessel image of the first image is shown by the following (Equation 2-1).
{(Α1-d1)-(β1-d1)} / {(α1-d1) + (β1-d1)}
(Equation 2-1)
Similarly, the contrast of the blood vessel image of the second image is shown by the following (Equation 2-2).
{(Α2-d2)-(β2-d2)} / {(α2-d2) + (β2-d2)}
(Equation 2-2)

Further, by multiplying one of the first image and the second image by the difference processing magnification k (assumed to be a positive constant), the contrast value of the difference image generated by these difference processing is calculated by the following (Equation 2-). It is shown in 3). Here, the pixel value of the blood vessel pixel in the difference image is α3, the pixel value of the fat pixel in the difference image is β3, and the minimum pixel value of the difference image is d3 (not shown).
{(Α3-d3)-(β3-d3)} / {(α3-d3) + (β3-d3)}
(Equation 2-3)

Based on the contrast value of the difference image of the above (Equation 2-3), which difference image is selected as the output image is determined. One aspect of the present invention, including the present embodiment, aims to extract a blood vessel image with high contrast by difference processing of a plurality of captured original images (images are selected based on blood flow fluctuation information).

It is preferable to select as the output image a difference image having a higher contrast value than at least the first image or the second image (that is, the one in the original image). Alternatively, it is also preferable to select a difference image having a contrast value higher than the contrast of all the original images. In this case, in the contrast evaluation of the original image, the original image having a positive blood vessel image contrast is evaluated as it is, and the original image having a negative contrast is evaluated for contrast again after the image is subjected to light-dark inversion processing. The difference image evaluates the contrast of the image in which the contrast becomes a positive value. Further, when there is an original image whose contrast value is higher than all the obtained difference images, the original image can be selected as the output image. Further, the above-mentioned contrast evaluation is also the same when the first image or the second image is an image generated by performing an averaging process or the like on a plurality of original images instead of one image.

At this time, the search for the value of the magnification k can be performed in a wide numerical range. However, when the value of the magnification k is extremely large or extremely small, the generated difference image is substantially close to the original image used for the difference processing, so that the contrast of the blood vessel image is also the original. There is a high possibility that the value will not be much different from the contrast of one image. According to what the present inventor has found, even when comparing images with different imaging conditions of the human body, for example, images with different imaging times and different blood flows, the fluctuation of the pixel value of a certain part is typically 2. It fits within twice. Therefore, the search range of k is preferably between 0.5 and 2.0, which is sufficient. Further, although the pixel value of the blood vessel image fluctuates greatly, the pixel value of the fat portion may not fluctuate significantly. For example, such a situation can occur when comparing two images whose shooting times are close to each other. In the difference processing between the original images in which the fat pixel value does not fluctuate significantly, it is possible to increase the blood vessel image contrast of the difference image even if the search range of k is between 0.9 and 1.1.

In addition, when evaluating and comparing the contrasts of the first image, the second image, and the difference image, it is necessary to unify the images in which the blood vessel image is bright and the fat part is darker than the blood vessel image. It is preferable from the viewpoint of easy viewing of the image. When comparing the contrasts, it is preferable to align the brightness and darkness of the blood vessel images between the images. This is because the contrast of the same image changes when the light and dark are reversed. In normal blood vessel transmission imaging, since the blood vessel is a light absorber, the blood vessel image appears dark and the fat part appears bright. For an image in which the blood vessel image is bright and the fat portion is dark, the normal transmission image may be inverted.

In the case of a difference image, either the blood vessel image becomes white and the fat part becomes dark, or the blood vessel image becomes dark and the fat part becomes bright, depending on the selection of the original image used for the difference processing and the value of the difference processing magnification k. The situation is also possible. Therefore, even in the case of the difference image, it is preferable to select an image in which the blood vessel image is bright and the fat portion is dark.

As the output image, the difference image selected as described above is used. Then, the same value is added to all the pixels so that the minimum pixel value is 0, and the maximum pixel value is a difference image generated by multiplying all the pixels by the same magnification so as to be the maximum value that can be displayed. By doing so, the output image to be generated can suppress so-called overexposure and underexposure, and has high contrast, which is preferable.

Further, when the first image and the second image are selected so as to maximize the value of the following (Equation 3), the blood vessel image intensity of the difference image can be maximized.
｜ (α1-k ・ α2)-(β1-k ・ β2) ｜ (Equation 3)
High contrast of the blood vessel image may be achieved at the same time by selecting the first image and the second image and selecting the difference processing magnification k so as to maximize the blood vessel image intensity of the formula 3. The contrast value of the blood vessel image in the difference image increases as the intensity of the blood vessel image represented by Equation 3 increases. At this time, when the minimum pixel value corresponds to the fat portion in the vicinity of the blood vessel for which the blood vessel image intensity is evaluated, the first image and the second image in which the blood vessel image intensity represented by the above formula 3 is maximized. The blood vessel image contrast is also maximized by selecting the difference processing magnification k. However, the minimum pixel value of the difference image does not always correspond to the fat portion in the vicinity of the blood vessel for which the contrast is evaluated as described above.

Further, by selecting the first image and the second image that maximize the blood vessel image contrast C of (Equation 3'), it is possible to maximize the blood vessel image contrast of the difference image.
C = {(α1-k ・ α2)-(β1-k ・ β2)} / {(α1-k ・ α2) + (β1-k ・ β2)} (Equation 3')

As will be described later, it is possible to increase the contrast of the blood vessel image in the difference image by determining an appropriate difference processing magnification k. Further, when paying attention to a certain pixel value, noise whose value fluctuates for each frame, such as camera noise and electrical noise, may be superimposed on the image. Therefore, when selecting the frame that maximizes (Equation 3), which is an example of the evaluation formula of the blood vessel image intensity, it is also preferable to consider that noise is superimposed on each pixel value. For example, let V be the value of (Equation 3) when the first image and the second image that maximize the value of (Equation 3) are selected. At this time, the noise superimposed on each pixel value is separately evaluated, and the value is set to N. At this time, since it can be considered that the value V includes an error due to noise of about ± N, when the maximum value of (Equation 3) is calculated to be V, the value of (Equation 3) is actually the value. If it is VN or more, it can be regarded as an almost maximum value.

Therefore, the selection of the first image and the second image having the maximum value of (Equation 3) is performed by selecting the first image and the second image having the value of (Equation 3) of VN or more. It is possible. In this case, if there are a plurality of candidates for the first image or the second image, any of those images may be selected as the first image and the second image, or they may be selected. An image obtained by averaging the images of the above may be generated separately. Further, the evaluation method of the noise value N possessed by a certain pixel can be read from the fluctuation of the pixel value of a specific pixel for each frame, for example, when shooting a moving image at the same wavelength. If the moving image is shot at a speed of several tens of fps to several fps, the frame rate is sufficiently high compared to the blood pressure fluctuation and pulsation of the human body. Therefore, high-speed pixel value fluctuations superimposed on a certain pixel value for each frame can be regarded as noise. It is possible to evaluate the standard deviation and fluctuation width of this pixel value fluctuation and calculate the noise value. Alternatively, for example, when dark noise, optical shot noise, or other specific noise is the main factor of the noise signal, those noise values may be measured separately and used as the noise value.

Alternatively, the fluctuation of the pixel value of the blood vessel pixel or the pixel value of the fat pixel for each frame is measured, low-pass processing or the like is performed to remove the temporal high frequency component, and the low frequency component is evaluated, and the above (Equation 3) or The first image and the second image having the maximum value of (Equation 3') may be selected. It is also preferable to evaluate a value obtained by averaging the pixel values in a region composed of a plurality of nearby pixels of blood vessel pixels and fat pixels. When the noise value is randomly generated temporally or spatially, it is possible to mitigate the influence of the noise by averaging the pixel values among neighboring pixels. In that case, the noise width decreases to N / √M in approximately inverse proportion to the square root of the number of pixels M used in the averaging process.

The value of the constant k is preferably 1 to simplify the arithmetic processing and enable high-speed processing, and it is also preferable to align the pixel values of the fat parts of the two images. For example, when the above-mentioned fat pixels (pixels of β1 and β2) are selected as the fat portion for aligning the pixel values, it is possible to set k = β1 / β2. With this setting, when a difference image is generated by maximizing the above (Equation 3), the pixel value of the fat part around the blood vessel image of the difference pixel can be set to 0, which is suitable for generating a high-contrast blood vessel image. .. However, since the minimum pixel value may be a negative value, it is preferable to confirm the minimum pixel value. When it is a negative value, it is preferable to perform a process of adding a certain value to the pixel values of all the pixels so that the minimum pixel value becomes 0.

In addition, when extracting the new blood vessel group generated near the joint of interest by differential processing, the optimum frame is selected by setting the above-mentioned blood vessel pixel and fat pixel at the position of the new blood vessel group and the fat part immediately beside it. It is possible to do. It may be the user of this device that sets the blood vessel pixel and the fat pixel. It is also preferable to automatically determine where in the image an artery, vein, or new blood vessel group is located by using software, and automatically set blood vessel pixels and fat pixels as appropriate. For example, a rod-shaped image can be regarded as an artery or a vein, or a technique such as pattern matching using an image of a subject once can be used to convert the blood vessel position / shape information of the first captured image into the second and subsequent captured images. It is also possible to recognize the included blood vessel image.

In addition, in a simple captured image before performing difference processing, the new blood vessel group may be faint and difficult to see. In such an image, a blood vessel pixel is set in the new blood vessel group and the fat portion in the vicinity thereof is set. It can be difficult to set fat pixels in. In this case, it is preferable to first perform a blood vessel image extraction process on the artery or vein near the joint of interest to generate an image. In this extracted image, there is a possibility that the new blood vessel group is extracted in an easy-to-see manner as compared with each original image before the difference processing. This is because when the new blood vessel group and the artery or vein are located close to each other, the timing of blood flow fluctuation is likely to be similar to each other.

Next, a case will be described in which a wide area including a plurality of joints such as the entire hand or the entire foot is simultaneously photographed to acquire an image of blood vessels in the vicinity of the plurality of joints or an image of a new blood vessel group. It is possible that the temporal aspects, including the timing of blood flow fluctuations, are not the same or similar between distant joints such as fingertip joints and wrist joints, or even between different joints of the same finger. However, in this embodiment, this is made similar. As a result, by focusing on the blood vessels in the vicinity of a certain joint and selecting the frame with the highest intensity of the blood vessel image or the difference processing magnification k as a result of the difference processing, the optimum frame selection and difference for other joints can be selected. There is a high possibility that it is a processing magnification. This also applies to the contrast of blood vessel images, and the set of frames and k that maximize the contrast of a certain blood vessel image and the set of frames and k that maximize the contrast of other blood vessel images are the same. there is a possibility.

Therefore, in the difference processing image, the problem that it is difficult to increase the contrast of the blood vessel image of one wide area of interest by one combination of the first image, the second image, and the difference processing magnification k is overcome. Will be done. In this way, it is possible to generate a difference image in which the blood vessel image has high contrast in a wide area including a plurality of blood vessels.

According to the present invention, it is not always necessary to set the ROI of interest, but a case where the ROI is set will be described. The area of interest ROI can be set in advance by the user, or can be automatically set by a computer. The larger the area of interest is set, the more uneven the time variation of the pixel value of the fat portion within the area of interest becomes, and the more likely it is that the pixel value of the fat portion varies from place to place (however, this can be solved by the present invention). is there). Therefore, the larger the region of interest, the more difficult it is to extract only the blood vessel image by cutting off the fat portion in the region of interest by the difference processing, and the possibility that the contrast of the blood vessel image in the region of interest decreases increases. Therefore, the target value Cd of the blood vessel image contrast is set in advance. Then, a certain region including the blood vessel of interest is set as the region of interest. In this state, the first image and the second image as the original image to be subjected to the difference processing and the set of the difference processing magnification k for maximizing the contrast of the blood vessel of interest are searched for, and the contrast C of the blood vessel of interest is calculated. .. Here, when C is larger than Cd, the new attention region is set wider than the preset initial attention region, and the blood vessel image contrast is also maximized in the first image, the second image, and the like. A set of difference processing magnification k is calculated. By repeating this operation, the maximum attention region can be set while maintaining the target value Cd for the contrast value of the blood vessel of interest, which is preferable. It is suitable for speeding up the processing to execute the steps of setting the region of interest, selecting the image for maximizing the contrast of the blood vessel image, and calculating the contrast of the blood vessel of interest, which are a series of operations.

On the contrary, when C is lower than Cd, it is also preferable to reset the attention region narrower than the preset attention region and recalculate the blood vessel image contrast. Further, the difference processing of the above images is not the difference processing between one image, and each image may be, for example, an average image of a plurality of images. In this case, for the selection of the image to be averaged, it is preferable to use the frames before and after including the frame extracted as being most suitable for the difference processing between one image, for example. For example, a frame that includes the most suitable frame and is earlier in time or a frame that is later in time may be selected. Alternatively, it may be a frame in a time zone before and after including a suitable frame.

The number of averaging processes can be set by the device user while looking at the difference image, and the S / N ratio is evaluated using the intensity of the blood vessel image as the signal value and the noise value as the random noise value, and then S / N. It is also possible to set it in the processing device so that the N ratio becomes equal to or more than a preset value. Further, it is also preferable to have a function of associating the operating time of the device with the acquisition time of the captured image, such as when a device such as a cuff is used to cause fluctuations in blood flow. This is not only for accurately knowing the time when the image was taken, but also for the extraction of blood vessel images because there may be a delay in the response of the human blood flow to external blood flow fluctuation factors. This is because it is useful information for selecting the optimum frame. It is also because it is difficult to estimate the operating time of an instrument such as a cuff from the data of the fluctuation of the pixel value due to the noise contained in the measurement data and the low reproducibility of the response of the human body. Furthermore, the time from the operation of the instrument to the change in blood flow at the imaging site may also differ depending on the site, so the above-mentioned associated function is a function suitable for optimal frame selection. It is also useful when the results are compared by performing multiple imaging so that the acquisition time of the two images to be subjected to the difference processing has the same time relationship as the time when the blood flow fluctuates due to blood vessel compression by the cuff or the like. Information, and the above-mentioned function is suitable.

Next, a case where blood vessel images of a plurality of sites are taken and blood vessel images are extracted will be described. First, the feature points of the present invention including the present embodiment will be described. As a result of the examination by the present inventor, it was found that when a large blood flow fluctuation is caused in the human body due to, for example, an external factor, the mode of the temporal change of the blood flow in the fat part is similar in different parts. .. That is, it is considered that the influence of the local blood flow fluctuation of the fat portion can be alleviated. For example, by attaching a tourniquet (cuff) to the upper arm and applying or releasing pressure, a rapid and large blood flow fluctuation occurs from the arm to the hand or finger. At this time, for example, large fluctuations in blood flow are induced at different joints of the same finger almost simultaneously. This is thought to mean the following: That is, a large fluctuation in blood flow caused by a fluctuation in the applied pressure of the upper arm greatly fluctuates the blood pressure supplied to each site at the terminal end. Therefore, for example, the blood pressure applied to the arterioles upstream of the capillaries in each part of the finger fluctuates greatly at the same time, and in response to this, the arterioles in each part further control the blood flow in the terminal capillaries. Be done.

Therefore, in order to clarify the blood vessel image in the difference image in a wide area such as the entire finger, a large blood flow fluctuation is caused as described above, and the mode of the blood flow fluctuation in the fat part in the wide area is made similar to the difference. It can be seen that the fat portion at any position should be similarly easily cut off by the treatment. This is because if the temporal changes of the fat part are similar at different positions, for example, the ratio of the pixel values in the frame A and the frame B is 1.05 times in the fat part at any position. .. The time to generate such a frame is when the above-mentioned large blood flow fluctuation occurs.

Large blood flow fluctuations are not necessarily due to external factors. As a result, it is only necessary that the blood pressure of the entire imaging site such as the hand fluctuates greatly at the same time. For example, when the imaging site is the left hand, the subject is given a light load by lightly raising and lowering the right hand on the opposite side. Due to this load, the heart rate and blood pressure may increase significantly when the right hand is moved, which leads to a large fluctuation in the blood pressure of arterial blood supplied to the entire left hand, which is the imaging site. .. Large blood flow fluctuations can be detected as a sudden change in transmittance of a blood vessel or a fat layer near it (a region of an imaging site) or a change in the amount of transmitted light. That is, it is possible to obtain blood flow fluctuation information by using information such as a change in transmittance, a change in the amount of transmitted light, or the timing of generation of blood flow fluctuation due to the above-mentioned tourniquet.

However, it has also been clarified by the study of the present inventor that this large fluctuation in blood flow lasts only for a limited time. That is, it is within a certain limited time that the blood flow fluctuations of the fat layers at different sites are similar. For example, in the case of fingers, this time is within about 1 minute. The cause of this duration is considered as follows. The large blood vessels that supply blood to the finger, in a rough approximation, run through the finger from the base of the finger to the tip. Now, for the sake of simplicity, we consider that there is only one thick blood vessel in the finger, and consider the time for the blood supplied from this one blood vessel to propagate in the capillaries of the finger and spread throughout the finger. Since the blood vessels of the finger pass in the longitudinal direction of the finger (the base of the finger ⇒ the tip of the finger), the supply of blood to the capillaries of the finger or the propagation direction of blood in the capillaries of the finger is in the thickness direction of the finger. Can be approximated.

It is known that the blood flow velocity in the capillaries is about 0.3 mm / sec to 1.0 mm / sec. On the other hand, since the thickness of the fingers is about 20 mm, the time for the blood flow in the capillaries of the fingers to propagate in the direction of the thickness of the fingers is about 20 seconds to 60 seconds (1 minute). From this, it is considered that the relationship between the blood flow propagation velocity in the capillaries and the size of the imaging site determines the duration of blood flow fluctuations associated with blood pressure fluctuations in the finger. That is, the duration of a large blood flow fluctuation at a certain site is about the time of the value obtained by dividing the crossing distance of the site by the blood flow velocity of the capillaries. When there are a plurality of thick blood vessels, it is considered that the time is about the value obtained by dividing the distance between the blood vessels by the blood flow velocity of the capillaries. Therefore, in order to obtain an image with high contrast of the blood vessel image in a wide part or region such as the entire finger, the frame for creating the difference image is an image or frame taken within the duration of the large blood flow fluctuation as described above. It is necessary to use.

Since the time change of the amount of transmitted light in the fat part is large when the duration of the large blood flow fluctuation is large, it is possible to determine the time when the pixel value change (time derivative value) in the transmission observation is large. Therefore, it is also possible to adopt a frame in which the pixel value change of transmission observation is rapid and large as a frame in which the blood flow change is large. Alternatively, it is also possible to set a threshold value of a predetermined transmitted light amount fluctuation value, and to detect a time when the blood flow fluctuation is large, assuming that the transmitted light amount fluctuation exceeding this is a large transmitted light amount fluctuation. Since the human body breathes about 20 times / minute in adults, if the amount of transmitted light fluctuates rapidly within 3 seconds, it can be regarded as a rapid blood flow fluctuation. If a change in the amount of transmitted light that is significantly larger than the change in the amount of transmitted light in normal times is shown even for about 3 seconds, it can be considered that this is the time when the change in blood flow is large.

As described above, in the frame of the time when the blood flow fluctuation is large, the blood flow fluctuation occurs in a wide area at almost the same time in the imaging region, so that the local blood flow fluctuation in the fat part is small and the fat part in the wide area is small. It can be expected that the ratio of the pixel values of is spatially substantially uniform between the two frames. Then, after causing such a blood flow fluctuation, the combination of frames of the difference image and the value of the difference processing magnification k are determined.

Examples of these determination methods include the following methods. A plurality of blood vessels of interest are set in a wide single area of interest in the difference image, and the contrasts of the plurality of blood vessels of interest in the difference image are c1, c2, ..., Ci, respectively. In the difference image using the frames within the duration of the blood flow fluctuation, the contrasts of these blood vessels of interest are calculated, and the set of frames that maximizes their average contrast and the difference processing magnification k are selected and determined. It is possible. Alternatively, it is also possible to employ a set of frames and a difference processing magnification k that maximize the contrast of the blood vessel image having the lowest contrast.

The selection of the first image and the second image (set of frames) and the setting of the magnification k are not limited to the method of determining by the average value of the contrast of each blood vessel image or the blood vessel image having the lowest contrast as described above. For example, it is possible to evaluate the variation in the contrast value of each blood vessel image by using a value such as standard deviation so that the contrast of any of the blood vessel images does not decrease extremely. For example, the target reference contrast value Ci is set in advance, the variation of the contrast of each blood vessel image from the Ci is expressed by the standard deviation, the frame set is selected so as to minimize the standard deviation, and the magnification k is set. Make settings. By setting the conditions for extracting a plurality of blood vessel images with high contrast under the same conditions in this way, it is possible to depict the blood vessel images of a wide portion of the imaging target with high contrast.

The difference processing of the above images is not the difference processing between one image, and each image may be an average image of a plurality of images. In this case, for the selection of the image to be averaged, it is preferable to use the frames before and after including the frame extracted as being most suitable for the difference processing between one image, for example. For example, a frame containing the most suitable frame and earlier in time may be selected, or a frame on the later side may be selected. Alternatively, it may be a frame in a time zone before and after including a suitable frame. The number of averaging processes can be set by the user while looking at the difference image, and the S / N ratio is evaluated by using the intensity of the blood vessel image as the signal value and the noise value as the random noise value. Can also be set by the processing device so that is greater than or equal to a preset value.

Further, when an instrument such as a cuff is used to cause fluctuations in blood flow, it is preferable to have a function of associating the operation time of the instrument with the acquisition time of the captured image. This is not only to know the exact time when the image was taken, but also because there is a delay in the response of the human blood flow to external blood flow fluctuation factors, which is the optimum frame for extracting blood vessel images. This is because it provides useful information for selection. It is also because it may be difficult to estimate the operating time of an instrument such as a cuff from the data of the fluctuation of the pixel value due to the noise contained in the measurement data and the low reproducibility of the response of the human body. Furthermore, the time from the operation of the instrument to the change in blood flow at the imaging site may also differ depending on the site, which is a suitable function for selecting the optimum frame. It is also useful when the results are compared by performing multiple imaging so that the acquisition time of the two images to be subjected to the difference processing has the same time relationship as the time when the blood flow fluctuates due to blood vessel compression by the cuff or the like. Information, and the above-mentioned function is suitable.

For example, when it can be confirmed that the brightness value of one area of the image changes according to the start of compression by the cuff and the release of compression by the cuff, that information is used. Normally, the brightness value increases (light absorption decreases) at the timing of cuff compression start, and the brightness value decreases (light absorption increases) at the timing of cuff release. The mode of change of the brightness value by the cuff may change in almost the same manner regardless of whether the pixel at the position of interest is a blood vessel site or a background site. Changes in blood flow due to cuffs appear as changes in vascular absorption contrast, but can also affect background absorption contrast. It is conceivable to select a frame in the change range in which the time derivative value of the luminance value is larger than a predetermined threshold value for the difference processing.

Next, the position of the blood vessel image for evaluating the blood vessel image contrast will be further described. As described above, it is considered that the arteries or veins existing nearby and the neovascularization group are similar in the mode of time change of the blood flow. Therefore, if the first image, the second image, and the magnification k, which have a large difference in blood flow between arteries or veins at a certain position, are selected, it is predicted that the difference in blood flow in the nearby neovascularization group will also be large. Will be done. That is, in order to extract a new blood vessel group near a certain joint, it is preferable to evaluate the blood vessel image contrast of the artery or vein near the joint and select a difference image having a high contrast of the blood vessel. Further, it is preferable to select the first image, the second image, and the magnification k that generate such a difference image.

Further, in the case of an artery or vein near the joint, it is conceivable that a group of new blood vessels exists in the immediate vicinity thereof, or a group of new blood vessels overlaps in the optical axis direction of the imaging optical system. In such a case, there may be a group of new blood vessels in a portion that is considered to be a fat portion on the side of the artery or vein when evaluating the strength of the artery or vein image. In that case, there is a possibility that the amount of change in the intensity of the artery or vein image in the plurality of images can be detected only by a small amount of change obtained by subtracting the amount of change in the pixel value of the new blood vessel group. Therefore, when it is considered that there is a high possibility that a new blood vessel group exists in a certain joint, in order to select and evaluate the optimum image for extracting the new blood vessel image, an artery that is not in the vicinity of the joint or It is also suitable to evaluate the vascular image contrast of the vein. Further, in order to improve the contrast of the neovascular group, it is also preferable to select the first image, the second image, and the magnification k such that the contrast is high in the artery or vein not near the joint.

The new blood vessels will be further described. Since the neovascular group is weakly absorbed and pale, it may not be found in the image before the difference processing. In this case, first, the difference processed image having the largest blood vessel image intensity of the difference image with respect to the artery or vein is generated. By this operation, the neovascular group image may be extracted and made easier to see. Therefore, if a new blood vessel group is found, the points for evaluating the pixel value are set again on the fat part above the new blood vessel group and around the new blood vessel group so that the image intensity of the new blood vessel group can be evaluated. It can be fixed. Then, as in the case of arteries or veins, it is also preferable to select the most suitable difference image for extracting a new blood vessel group, a set of original images, or a difference processing magnification k.

In addition, the new blood vessel group has a structure different from that of blood vessels that are always present in the human body, such as aorta, arteries, arterioles, vena cava, veins, venules, and capillaries. Therefore, even if pressure is applied in the same manner as these blood vessels, the magnitude and speed of blood flow fluctuations that occur at that time may differ. For example, there may be a case where the blood flow fluctuation of the new blood vessel group occurs a little after the blood flow fluctuation of the artery or vein. In addition, even if the arteries and veins that are apparently close to each other and the new blood vessel group are located, it is highly possible that the distances from the blood flow changing means such as the heart or the cuff are different. For this reason, changes in blood flow in the neovascular group may occur earlier. Therefore, when a large number of blood vessel images are acquired in time by video recording or the like, arteries or veins are extracted by difference processing, and new blood vessel groups are extracted before and after the frame near the frame set that makes it most visible. It is also preferable to search for a suitable set of frames.

It will be described that the processing may be terminated at an appropriate time point. As the shooting work progresses and the image data is acquired, the acquired images are sequentially processed, and the above-mentioned (Equation 2-1), (Equation 2-2), and In some cases, the contrast is evaluated according to Equation 2-3). In this case, it is also preferable to end the shooting when the evaluated value reaches a certain value or more (that is, when a predetermined condition is satisfied). Alternatively, it is also preferable to have a function of notifying the end of shooting. With this function, it is possible to finish the imaging of the subject in the minimum necessary imaging time, and it is possible to avoid an increase in the load on the user of this device and the subject, which is preferable.

Further, it may have a function of evaluating the intensity of the blood vessel image based on (Equation 2-1) and ending the imaging when the intensity exceeds a certain value. In order to keep the S / N ratio of the blood vessel image in the difference image large, it is preferable that the blood vessel image intensity of the difference image is a large value. Therefore, by measuring the noise value N in advance, the desired blood vessel image intensity or It may have a function of ending the measurement when the S / N ratio is reached. This is the same not only when one blood vessel image is evaluated for contrast but also when a plurality of blood vessel images are evaluated. It is also preferable to have a function of ending the measurement when the average value of the contrasts of a plurality of blood vessel images, the contrast value of the lowest contrast blood vessel image, or the like reaches a certain value or more.

As a shooting flow using a cuff, a step of "normal shooting ⇒ shooting with the cuff tightened ⇒ shooting with the cuff tightened released" is assumed. In the process, the number of shooting frames increases as time passes. When generating a difference image from a group of shooting frames, there is a method of generating a difference image after shooting all the frames. On the other hand, there is also a method of generating a difference image in real time as the number of shooting frames increases. The method of ending the process at an appropriate time point is performed with the following intention. That is, in the process of shooting, a difference image that can be created by sequentially combining "shooting frames already acquired at that time" is generated. Then, if there is an image that achieves a desired contrast among these difference images, the shooting flow may be terminated at that point.

As a method of generating the final output data after the above processing, there is a method of selecting and processing a single image from a plurality of acquired image data. In addition to this, a processed image that has undergone averaging processing or the like is separately generated for the selected single image and another image whose shooting conditions are close to each other, and these processed images are calculated to generate the final image. It is also possible to do. Examples of close shooting conditions include close shooting times or close shooting wavelengths. Further, it is also possible to create a processed image group in which noise removal processing and averaging between images are performed in advance on a plurality of captured image data. Then, a plurality of images are selected from these processed image groups based on the blood flow fluctuation information to obtain the first image and the second image, and these images and the magnification k are used to generate a final difference image. It is also preferable to extract a blood vessel image.

According to this embodiment, it is possible to generate a blood vessel image in which scattered light in a living body is suppressed, which makes it easy to grasp the shape and position of blood vessels. However, the output of this device is not limited to the image, and may be the result of extracting certain information from the image data or the judgment value of the disease. For example, the pixel values on a certain line segment in the image data and the data obtained by graphing the distribution thereof may be used.

Alternatively, it may be a detection result such as the presence or absence of specific data or data having a specific feature. For example, it is possible to photograph a certain area such as a joint, calculate the average of the pixel values of the area including the joint for each joint, and compare it with other joints. Then, it is possible to detect the presence of a specific site suspected of having a disease or injury, such as a particularly low or high average pixel value as compared with other joints, from the imaging data. When it is detected, it is possible to perform processing such as displaying a message notifying that a specific part has been detected or a determination result as an output from the device. Since such processing directly processes and calculates the shooting data without going through the processing of converting the shooting data into an image, high-speed calculation is possible.

An example of each part of the information acquisition device and the photographing device for performing the above processing will be described in detail.
"light source"
An LED or a laser can be used as the light source for irradiating the imaged portion with light. The wavelength region of the irradiation light is preferably in the visible to infrared to near-infrared band for biological imaging, and in particular, near-infrared light having a wavelength of 1400 nm or less is preferable because it has a high depth of penetration into the living body. A light source having a large area is suitable so that the imaging area can be collectively irradiated with the irradiation light, and this can be realized, for example, by forming a surface light source in which LEDs are arranged in an array. Alternatively, it is also preferable to irradiate with a thick parallel light beam. If it is an LED, it can be realized by collimating one LED to a substantially parallel luminous flux. If it is a laser, it can be realized by expanding the luminous flux diameter to make it a parallel luminous flux.

A configuration in which a diffuser plate is inserted between the illumination light source and the photographing portion is suitable because it is possible to make the light amount distribution of the light source such as an LED array uniform and irradiate the imaged object. When a laser is used as an illumination light source, it is possible to take a picture while changing the irradiation position using a scan optical system such as a galvano mirror while keeping the point light source without enlarging the luminous flux diameter. The advantages of using point irradiation and scanning optics are that it is possible to accurately irradiate the desired irradiation position, the sweep speed or staying time of the irradiation position, and the light amount modulation of the light source itself can be used to realize a precise light amount distribution. Is mentioned. Since the luminous flux diameter is small and it is easy to block light, it is also preferable that leakage light and stray light can be easily suppressed.

Further, scanning the light receiving position synchronized with the scanning system of the light source is preferable because it is possible to extract only the component close to the straight component from the light propagating in the scattering body such as a living body. As the scanning system, a galvanometer mirror, an iris or a slit capable of high-speed position scanning may be used.

In the case of an unpolarized light source such as an LED, it is also possible to insert a first polarizer between the light source and the imaging portion to provide polarized illumination. In this case, by inserting a second polarizing element between the imaged portion and the receiver, it is possible to detect the polarization component of the light transmitted through the imaging portion. Further, LEDs having different emission wavelengths may be arranged in an array to form a light source that emits light at a plurality of wavelengths. Alternatively, a light source whose emission wavelength changes with time may be used. By using such a light source, it is possible to acquire blood vessel images taken at different wavelengths.

Before shooting, the optimum shooting wavelength may be found for each person to be photographed or each part to be photographed. The oxygen saturation of human blood is considered to be different from place to place, and as a result, the absorption spectrum of blood is also expected to be different from place to place. Therefore, how much the blood vessels absorb light and how dark the image appears in normal imaging depends on the imaging wavelength. Further, when a blood vessel image is generated by performing difference processing between the captured images, it is considered that the contrast of the blood vessel image also depends on the imaging wavelength. It is also possible that the intensity of the sunburn on the skin and the intensity of light scattering by the fat layer differ depending on the subject. Therefore, it is considered that the blood vessel image contrast in the difference image is wavelength-dependent as described above.

As a method of finding the wavelength at which the contrast of the blood vessel image generated by the difference processing is highest, for example, the imaging wavelength is actually changed, multiple images are taken, and the blood vessel image is generated by the difference processing between the images of each wavelength. And it is possible to compare their contrasts. However, in this method, in order to search for the optimum shooting wavelength, the actual shooting work is required as many times as the number of wavelengths to be shot, so that it may take a long time to shoot. Further, when the time for acquiring an image differs greatly depending on the wavelength, there is a possibility that the state of blood flow in the imaged portion may change while the imaging work at each wavelength progresses. It is difficult to distinguish whether the change in the contrast of the blood vessel image of the captured image at each wavelength is due to the difference in the imaging wavelength, or whether the blood flow rate is different and the density of the blood vessel image appears to change due to the different shooting time. Can be an issue.

On the other hand, in order to shoot at different wavelengths at the same time, the part to be photographed is irradiated with a light source capable of simultaneous emission at multiple wavelengths, and the camera is a spectrum at each position, for example, a hyperspectral camera. It is possible to use a camera that can obtain information. Alternatively, it is also possible to divide the optical path on the detection camera side for each different wavelength by a spectroscopic element such as a dichroic mirror, and arrange a normal photographing camera for each optical path for each wavelength. However, a configuration using a hyperspectrum or a plurality of cameras may be expensive, or the optical system may be complicated and large.

Therefore, using a configuration that combines a normal shooting camera, a single shooting optical system, and a light source as described in this explanation, a method that enables shooting in a state where the blood flow state is close at all wavelengths to be shot is used. Presented below.

First, the device configuration will be described. As the light source to irradiate, a light source capable of changing the emission wavelength with time is used. As an example of such a light source, for example, in the light source 801 in which LEDs having a plurality of wavelengths are arranged in a matrix as shown in FIG. 11, the emission wavelength changes with time by sequentially switching the lighting LEDs. An LED light source can be mentioned. The light source 801 is composed of an LED 802 having a center wavelength λ1, an LED 803 having a center wavelength λ2, and an LED 804 having a center wavelength λ3. Only the LED 802 is lit at one time, only the LED 803 is lit at another time, and only the LED 804 is lit at another time. The light source is not limited to this configuration, and may be a wavelength sweep laser or the like. Then, as the photodetector, a photographing camera having sensitivity to the photographing wavelength is used.

Next, a shooting method will be described. In the optimum imaging wavelength search method in the present description, an artificial blood flow fluctuation is caused by using a cuff or the like as in the main imaging. From the findings of the present invention, it was found that when an artificial blood flow fluctuation is caused by using a cuff or the like, the time during which the blood flow fluctuation at the imaged site is large is within a certain time from the operation time of the cuff. .. It is about the same as the time required for the blood flow in the capillaries to propagate through the distance of the part to be imaged. Typically, for the fingers of the human body, the passing distance is about 20 mm and the blood flow in the capillaries is about 0.3 / mm, so that 1.0 / mm is within about 1 minute. By avoiding the time when the blood flow fluctuation is large, it is possible to take a picture at the time when the blood flow fluctuation is relatively small. Therefore, examples of times when blood flow fluctuation is small are (1) normal state before cuff tightening operation (state where nothing is tightened), (2) time 1 minute or more after cuff tightening, and (3) cuff tightening. There are three time zones, one minute or more after being released from the state.

In at least two time zones from these, images are taken with different light source wavelengths, and the obtained images having the same wavelength are subjected to difference processing. For example, in the case of shooting at three different wavelengths in each of the three time zones (1), (2), and (3), the procedure is to turn on the LEDs of the three wavelengths in sequence in the time of (1) and each wavelength. The blood vessel image is taken with, and this is done in the same manner at the time of (2) and the time of (3).

In the shooting in each of the time zones (1), (2), and (3), the number of shot images at each wavelength is not limited to one. Multiple sheets may be used. If a plurality of images are taken, random noise can be reduced by averaging those images. However, for example, when five blood vessel images are taken at each wavelength, it is preferable that the shooting work at each wavelength is performed alternately with respect to the wavelength. In other words, "1st sheet of wavelength 1 ⇒ 2nd sheet of wavelength 1 ⇒ ... ⇒ 5th sheet of wavelength 1 ⇒ 1st sheet of wavelength 2 ⇒ 2nd sheet of wavelength 2 ⇒ ... ⇒ 5th sheet of wavelength 2 ⇒ wavelength 3 The next shooting order is preferable to the shooting order of "first shot ⇒ ...". That is, the shooting order of "1st image of wavelength 1 ⇒ 1st image of wavelength 2 ⇒ 1st image of wavelength 3 ⇒ 2nd image of wavelength 1 ⇒ 2nd image of wavelength 2 ⇒ 2nd image of wavelength 3 ⇒ ..." Is preferable (Fig. 12).

When searching for the optimum shooting wavelength, the blood flow state changes during that time because the shooting time of each wavelength is different, and it becomes impossible to distinguish between the contrast fluctuation of the blood vessel image due to the difference in wavelength and the contrast fluctuation due to the blood flow fluctuation. I want to avoid that. Therefore, it is preferable that the shooting times at each wavelength are as close as possible. When a plurality of shots are taken at each wavelength, it is preferable to use the above-mentioned shooting order because the average time of the shooting times of each wavelength can be made as close as possible. In addition, when multiple images are taken by oscillating the shooting wavelength, the exposure time per image is taken at any shooting wavelength because of the wavelength dependence of the sensitivity of the camera and the wavelength dependence of the transmittance of the living body. It is preferable to adjust the amount of irradiation light so that It is assumed that the exposure time required for shooting one image is Δt [seconds] because the exposure time is the same for shooting at any wavelength. At this time, for example, it is possible to set the frame rate to 1 / Δt [fps] by setting the camera in the moving image shooting mode, and it is possible to easily perform angiography with different wavelengths at high speed, which is preferable.

There are the following three ways to select the two time zones, but it is particularly preferable to use images in the time zones (1) and (2) or the time zones (2) and (3). First, when the difference processing is performed on the images of (1) and (2), there is an advantage that the shooting work can be completed early because it is not necessary to continue shooting until the time of (3). Furthermore, (1) is the time zone when the blood flow is large because the cuff is not tightened, and (2) is the time zone when the blood flow is small due to the cuff tightening, so the image of the time zone (1) and (2) The images of the time zone may have very different blood vessel image density. If the blood vessel image is extracted by performing the difference processing of such an image, there is a high possibility that a blood vessel image having high contrast can be generated.

In addition, when the difference processing is performed on the images of (2) and (3), as in the case of (1) and (2), (2) and (3) are time zones in which the blood flow is significantly different from each other. There is a possibility that the density of the blood vessel image differs greatly between the image in the time zone of 2) and the image in the time zone of (3). If the blood vessel image is extracted by performing the difference processing of such an image, there is a high possibility that a blood vessel image having high contrast can be generated.
Further, since both (2) and (3) are in the time zone when the artificial blood flow fluctuation due to the cuff is strongly generated, the influence of the blood flow fluctuation due to the control of the human body itself is unlikely to occur, which is suitable.

As a result of the above imaging, a difference image is generated at each of a plurality of wavelengths, and the contrast of the blood vessel image is compared. Then, the wavelength having the maximum blood vessel image contrast is determined to be the optimum imaging wavelength. For example, if five images are taken at each time of (1), (2), and (3) at each wavelength, the images of each wavelength at times (1), (2), and (3) are aligned with each other. To generate an image that has been averaged within each of the times (1), (2), and (3). This is performed for each wavelength, and one image of each wavelength is generated for each time of (1), (2), and (3). After that, the ROI is set, the blood vessel pixel, and the fat pixel are set in the image of each wavelength, and the difference processing is performed between the images of the same wavelength. At this time, the difference processing magnification that maximizes the contrast of the blood vessel image in the ROI is searched for and the contrast is obtained in the same manner as in the main imaging described above.

In the above determination of the optimum shooting wavelength, the method of selecting the frame used to generate the difference image is not "the frame for obtaining the maximum contrast". The main purpose is to select "a frame in a time zone in which the blood flow hardly changes during shooting at each wavelength, although the shooting time is slightly different for each wavelength". Further, in the above optimum wavelength search, it is assumed that when images are taken in the same blood flow state for each wavelength, the wavelength that maximizes the blood vessel image contrast of the difference image for each wavelength generated from these images. Assumes that in other blood flow conditions: That is, even if the frame used for generating the difference image is selected so as to maximize the contrast of the blood vessel of interest in the ROI, it is the wavelength that maximizes the blood vessel image contrast of the difference image.

In the above optimum wavelength search, the following is also suitable. When the wavelength of the light source is, for example, a wavelength near 800 nm at which the absorption of hemoglobin and oxidized hemoglobin are substantially equal, both arteries and veins can be photographed, which is preferable. Further, a set of wavelengths around 800 nm is also preferable. This is because the imaging is performed at a wavelength at which the artery is emphasized and a wavelength at which the vein is emphasized, which makes it easier to distinguish between the artery and the vein.

As a method for determining a time zone in which there is little change in blood flow, in addition to the method of determining after a certain period of time after the cuff operation as described above, it is also good to select a time zone in which the fluctuation of the pixel value is small. For example, there are the following methods for determining a frame group in which the fluctuation of the pixel value is small. Pixel value fluctuations due to sudden blood flow fluctuations due to cuff operation are typically about 10% in the case of fingers. Therefore, a time zone in which the blood flow fluctuation value sufficiently smaller than this, for example, the fluctuation range of the pixel value is within 1% or less of the pixel value at that time, is a time zone in which the blood flow fluctuation is small. It is possible to determine that.

《Holding stand》
A holding table having a function of holding the imaged portion of the subject may be provided. It may be a simple planar shape, or it may be a curved surface shape that matches the shape of the imaging portion. For example, when the imaging part is a hand, the method of holding the imaging part differs depending on whether the optical path of the imaging optical system is vertical or horizontal. Therefore, the holding trapezoidal shape is appropriately suitable for the optical path of the imaging optical system. Is preferable.

When the irradiation light is transmitted through the holding table and the imaging portion, it is desirable that the holding table is made of a member having a high transmittance with respect to the irradiation light. It is also preferable that a part of the holding table is made of a light transmitting member or a transparent member such as air, and the remaining part is made of a light shielding member, so that the illumination light irradiates only a desired position of the photographing portion. Further, it is preferable that the holding table has a structure in which the holding height of the imaging portion is variable according to the physique of the subject, the height of the heart, and the like. It is also preferable to have a function of changing the holding height for each image to be captured. With such a configuration, the height relationship between the heart and the imaging site changes for each captured image, and the blood pressure at the imaging site also changes accordingly, so that the blood flow rate differs for each captured image and the blood vessels. Images with different intensity of light absorption can be obtained.

The temperature of the holding table may be variable. When the holding table is slightly warmer than the body temperature, the imaged part of the subject is also warmed, so that the blood flow rate of the imaged part can be increased. This may result in a darker blood vessel image. On the contrary, when the holding table is lower than the body temperature, the temperature of the imaging site also decreases, so that the blood flow rate of the imaging site may decrease. As described above, by having the function of changing the temperature of the holding table, it is possible to acquire an image in which the blood flow rate is different for each photographed image and the intensity of light absorption by the blood vessel is different.

《Camera (detector)》
As the photodetector, a camera, a photodetector, or the like having sensitivity to the shooting wavelength is used. As a photodetector, it is possible to use a camera capable of acquiring an image. For example, in the case of a camera capable of outputting digital data, the output can be finally taken into a processing device as digital image data. Since the blood vessel image inside the living body is surrounded by scattering bodies such as fat, muscle, and bone, the scattered light in the living body is superimposed and becomes a faint image. Therefore, when a camera is used for photographing a blood vessel in a living body, it is preferable that the camera has a rich gradation and has a performance capable of reliably detecting a distribution of a small amount of light. It is preferable that the noise of the camera is also small.

Further, the camera may have a function of shooting a moving image in addition to a camera having a function of shooting a still image. The photodetector may be used as a photodetector, and the acquired image may be reconstructed in the computer from the light receiving position signal and the light intensity signal in combination with an optical system or an optical element that scans the light receiving position. Since the voltage signal from the photodetector is an analog output, it is preferable to perform AD conversion with a high number of bits when AD converting the voltage signal and incorporating it into an arithmetic unit such as a computer. Since the photo detector is a single element, it is excellent in high speed and low noise, and is suitable.

<< Processing equipment >>
In the processing device, an image obtained by extracting a blood vessel image is generated based on a signal from a photodetector such as a camera. The processing device may be, for example, a computer. If necessary, it may have an capture board that captures a signal from a photodetector. It is also preferable to have a display for displaying a photographed image and a final image calculated by various arithmetic processes. The configuration is not limited to displaying an image on a display, and information such as an image may be displayed on another display device.

The processing device has a built-in program or application that enables various arithmetic processes on the image. You may have a board or the like on which these programs are mounted as a circuit. At the same time, the processing device may also have a light source control function (monitoring of light amount fluctuation, suppression, light amount adjustment, wavelength selection, etc.) and a control function of a holding table.

(Example 1)
Hereinafter, a photographing apparatus including the information acquisition apparatus according to the first embodiment of the present invention will be described with reference to FIG. FIG. 5 is a schematic view showing an apparatus according to this embodiment. The photographing device is provided with a light source 501, a holding table 502, a photographing camera 503, a light source driving power source 504, a control processing PC 505, and a monitor 506. The inspection object to be imaged indicates the finger 507. A tourniquet is attached to the upper arm (not shown) between the finger 507 and the heart, and the applied pressure is controlled by a signal from the control processing PC.

The light source 501 irradiates the finger 507 with light having a wavelength of 810 nm, the photographing camera 503 detects the light transmitted through the hand, and generates an image signal based on the detected light. Here, the light source 501 is an array of LEDs having a wavelength of 810 nm. The photographing camera 503 is a camera having sensitivity to light having a wavelength of 810 nm and outputs a digital signal. Further, the photographing camera shoots a moving image of 10 frames per second for 160 seconds, and acquires each frame as image data.

At the start of imaging, the applied pressure in the tourniquet is 0 mmHg. Next, when 30 seconds have passed from the start of imaging, pressure is applied to the tourniquet zone up to 160 mmHg in 5 seconds. Then, the applied pressure is returned to 0 mmHg in 5 seconds from the time when 60 seconds have passed after the pressure is applied. After that, shooting is performed for another 60 seconds, and the shooting is finished. FIG. 6 shows the relationship between the applied pressure and the time depending on the operating state of the tourniquet at this time. The applied pressure in the tourniquet is controlled from the control process PC505.

The control processing PC 505 captures the image signal generated by the photographing camera 503. The control processing PC 505 generates image data based on the captured image signal, and displays the generated moving image or the image of each frame on the monitor 506. As a result, the operator can confirm the imaging result of the blood vessel of the joint of interest, which is the imaging target of the finger 507 displayed on the monitor 506.

Further, the control processing PC 505 performs an alignment calculation process of the blood vessel images of the images of the second and subsequent frames with respect to the blood vessel images of the first frame with respect to the images of the blood vessels of each frame taken. However, the frame used as the reference for the alignment of the blood vessel image is not limited to the first frame. As a result, the image of each frame corrects the misalignment of the blood vessel image due to the movement of the subject's hand that occurs during shooting, and the blood vessel image becomes an image recorded at the same position. Further, an averaged alignment image is generated by averaging 10 alignment images at a time. An averaged alignment image obtained by averaging the 1st to 10th images with respect to the 1600 images taken ..., an averaging of the 1591 to 1600th images. Generate an aligned image.

Further, the control processing PC 505 evaluates and stores the intensity of the photographed blood vessel image 508. First, the user sets the ROI 509 in the averaged alignment image. The setting of ROI509 can be omitted. Then, in order to evaluate the contrast of each blood vessel in this, the pixels of the first region on each blood vessel image 520, 522, 524, 526, 528 and the pixels of the second region of each fat portion in the vicinity thereof. 521, 523, 525, 527, 529 are specified.

Next, the control processing PC 505 reads and stores the values of the pixels 520, 522, 524, 526, 528 and the pixels 521, 523, 525, 527, and 259 in each frame. Further, the lowest pixel value in ROI509 is also extracted and stored. Then, the averaged alignment image including the frame within 60 seconds after the cuff operation (within 1 minute after the operation) is selected as both images. After the cuff operation means after or immediately after the operation of compression or compression release by the cuff. For each combination, the value of the difference processing magnification k is changed from 0.5 to 2.0 in increments of 0.01, and each difference image data is generated for all the combinations. In each difference image, a set of frames having the lowest contrast of the blood vessel image of 0.3 or more and a difference magnification k among the contrasts of a plurality of sets of pixels in the first region and pixels in the second region are selected. Among them, a set of averaged aligned images having the highest average contrast of a plurality of sets of contrasts and a difference magnification k are selected. Then, a difference image between these images is generated and displayed on the screen. In order to speed up the processing, it is possible to evaluate the blood vessel image contrast of the difference image by the difference processing between one image instead of the generation of the averaged alignment image and the contrast evaluation by the averaged alignment image. good.

The averaged alignment image may include at least one frame within 60 seconds after the cuff operation. That is, another frame may be a frame other than 60 seconds after the cuff operation. It cannot be adopted that the frame is not included at all within 60 seconds after the cuff operation, but if it is included even a little, the blood vessel image becomes clear to some extent. However, it is more likely that the blood vessel image becomes clearer when there are more frames within 60 seconds after the cuff operation than when there are few frames.

The optimum image A and image B and the difference processing magnification k are selected by the contrast evaluation. Then, with respect to the image A selected in the above step, in addition to the image A, a total of 10 images including 4 images having a shooting time before the image A and 5 images having a continuous shooting time after the image A. Generate image A'averaged with images. Image B is also processed in the same manner to generate an averaged image B'. Then, a difference image between the image A'and the image B'is generated. For this as well, the contrast may be calculated in the same manner as described above.

The control processing PC 505 can control the amount of light of the light source 501 by using the light source drive power supply 504. Further, the control processing PC 505 can appropriately adjust various shooting conditions such as the sensitivity and the exposure time of the shooting camera 503. By these operations, it is possible to photograph the blood vessels of the joint of interest with high contrast.

If an image considered to be a new blood vessel group is found in the image or in the ROI other than the artery or vein, the analysis process is further continued. Pixels in the neovascular group (not shown) and pixels outside the neovascular group that are neither arteries nor veins (not shown) are specified by the user or the control processing PC, and the pixel values of the former pixels in each image are used. The pixel value of the latter pixel is extracted. Then, the image C, the image D, and the difference processing magnification k that maximize the contrast of the blood vessel images represented by both pixels are found, averaged with 10 images in the same manner as the images A and B, and the images C'and D' And. Then, a difference image between the image C'and the image D'is generated. By this operation, an image or related information of a new blood vessel group can be extracted.

The operation of the modified example of the above embodiment will be described with reference to the flowcharts of FIGS. 8 to 10. First, it will be described with reference to the flowchart of FIG.
(Step 1)
As described above, a plurality of original images are shot under different shooting conditions.
(Step 2)
As described above, in each case, a plurality of averaging source images including the image data selected based on the blood flow fluctuation information are generated. These are used in the process of the next step 3.

(Step 3)
Generate a difference processed image of the averaged image. The difference image to be generated is an image generated by the following two operations, where k is a coefficient. The difference image is defined as the difference between one and the other by a factor of two, using two of the original images.
Difference image = averaged image 1-k x averaged image 11
Difference image = averaged image 11-k x averaged image 1
Further, these images are generated by varying the value of k between 0.5 and 2.0 in 0.01 increments. Then, the same operation is performed on different averaged images to generate a difference image. These difference images are stored in the storage unit of the control processing PC.

In this way, a large number of difference images are generated and held in the processing unit by changing the difference processing magnification with various sets of original images. It is possible to hold only the related information (the above data set) instead of the difference image data itself, and create the difference image data based on the related information (the above data set) when necessary.

(Step 4)
Further, the control processing PC 505 evaluates the blood vessel image contrast in the generated difference image. As shown in FIG. 5, first, in order to evaluate the contrast of each blood vessel in the difference image, a pixel on each blood vessel image and a pixel of each fat portion in the vicinity thereof are designated. Here, each of the above points is arranged near the knuckles. Each pixel is specified by a single pixel. The blood vessel pixel is set in the central portion in the thickness direction of each blood vessel, and the pixel in the fat portion predicts that the blur due to scattering of the blood vessel image is about 1 mm, and the direction from the blood vessel pixel is substantially orthogonal to the traveling direction of the blood vessel. Set at a point 1 mm away. Then, the pixel value of the pixel is acquired. Further, the minimum pixel value (not shown) is also acquired. Based on these acquired pixel values, the contrast of blood vessels is calculated and evaluated.

(Step 5)
The difference image that maximizes the average of the blood vessel image contrast is selected. In this way, based on the blood vessel contrast of the difference image, the difference image for generating the output image is selected from the plurality of difference images and associated with each other.

(Step 6)
Next, an output image is generated. The output image is generated as follows. The same value is added to the pixel values of all the pixels so that the minimum pixel value of the associated difference image is set to 0. Further, the same magnification is multiplied by all the pixel values so that the maximum pixel value becomes the maximum value that can be displayed. In this embodiment, data processing is performed in 8 bits, and the maximum displayable pixel value is 256. Therefore, all pixels are multiplied by a magnification such that the maximum pixel value is the pixel value 256. In this way, the output image is generated using the associated difference image.

In the above process, the control processing PC 505 can control the amount of light of the light source 501 by using the light source drive power source 504. Further, the control processing PC 505 can appropriately adjust various shooting conditions such as the sensitivity and the exposure time of the shooting camera 503. By these operations, it is possible to photograph the blood vessels of the joint of interest with high contrast.

Furthermore, if an image considered to be a new blood vessel group is found other than the artery or vein, the analysis process can be continued. Pixels in the new blood vessel group (not shown) and pixels outside the new blood vessel group that are neither arteries nor veins (not shown) are specified by the user or the control processing PC, and the minimum pixel value is also grasped to grasp the new blood vessel. The contrast of the group is calculated in the same manner as for normal blood vessels. Then, the difference image having the highest contrast of the neovascular group is selected, and this is used as the final output image.

That is, as shown in step 7 of the flowchart of FIG. 10, in the blood vessel image (image that makes the blood vessel image easy to see) generated in step 6, at least one of the blood vessel pixel and the fat pixel is set at a different position. You can start over and start over from step 4. By using the information acquisition device of this embodiment, an image obtained by extracting the blood vessel image 508 can be obtained.

Another example will be described with reference to the flowchart of FIG. 9 similar to that of FIG.
(Step 1)
It is performed in the same manner as in the above embodiment.
(Step 9)
Next, the control processing PC 505 generates an alignment image in which the blood vessel images are aligned with each other with respect to the image of the blood vessel of each frame taken. The blood vessel images are aligned with each other from the first frame to the 1600th frame with respect to the 1600 images taken, and the aligned images from the first frame to the 1600th frame are generated respectively.

(Step 3)
It is done in the same way as above.
(Step 14)
Further, the control processing PC 505 evaluates the generated difference image and the blood vessel image contrast in the aligned image used for generating the difference image. First, in order to evaluate the contrast of each blood vessel in the difference image and the aligned image, a pixel on each blood vessel image and a pixel of each fat portion in the vicinity thereof are designated. Again, each of the above points is placed near the knuckles. Each pixel is specified by a single pixel. The blood vessel pixel is set in the central portion in the thickness direction of each blood vessel, and the pixel in the fat portion predicts that the blur due to scattering of the blood vessel image is about 1 mm, and the direction from the blood vessel pixel is substantially orthogonal to the traveling direction of the blood vessel. Set at a point 1 mm away. Then, the pixel value of the pixel is acquired. Further, the minimum pixel value (not shown) is also acquired.

The contrast of blood vessels is evaluated from these acquired pixel values. Then, the difference image having the maximum average value of the blood vessel image contrast is selected. Further, it is confirmed that the difference image has a higher contrast than the 1600 captured images that have been aligned. In the evaluation of the blood vessel image contrast of the captured 1600 images, when the contrast becomes a negative value, an image obtained by inverting the brightness of the image is generated. Then, the blood vessel image contrast is recalculated by setting the blood vessel pixel and the fat pixel and evaluating the pixel value of the minimum pixel for the image.

(Step 15)
Next, an output image is generated. As the output image, the blood vessel image contrast of the difference image having the maximum average value of the blood vessel image contrast is compared with the blood vessel image contrast of the 1600 captured images, and the image having the largest blood vessel image contrast is associated. ..

(Step 16)
The same value is added to the pixel values of all the pixels so that the minimum pixel value of this image is set to 0. Further, it is generated by multiplying all the pixel values by the same magnification so that the maximum pixel value becomes the maximum value that can be displayed. In this example as well, data processing is performed in 8 bits, and the maximum displayable pixel value is 256. Therefore, all pixels are multiplied by a magnification such that the maximum pixel value is the pixel value 256.

As in the example of FIG. 8, the following may be performed. That is, as shown in step 7 of the flowchart of FIG. 10, in the blood vessel image (image that makes the blood vessel image easy to see) generated in step 16, at least one of the blood vessel pixel and the fat pixel is set at a different position. Start over and start over from step 14.

505: Control processing PC (Parts 1 to 4), 508: Blood vessel

Claims (31)

It is an information acquisition device that acquires a blood vessel image of a blood vessel included in the imaging site by combining it with a blood flow changing portion that is arranged outside the imaging site and changes the blood flow of the imaging site.
The first part of acquiring a plurality of image data including the imaging site in the imaging region corresponding to a plurality of imaging times in which the operating state of the blood flow changing portion is different , and
Generating a difference processed difference of image data between different image data selected from a selected plurality of image data to include image data obtained in response to shooting time immediately after the operation of the blood flow changing portion Part 2 and
In the difference image data and the plurality of image data, a first region that is a part of a region corresponding to a blood vessel and a part of a region adjacent to the first region and other than the region corresponding to the blood vessel. In the second area, and in the third part, which acquires index data using the data in
Based on the index data, from the difference image data and the image data group including the plurality of image data , the relationship between the image data including the contrast-enhanced blood vessel image or the image data including the contrast-enhanced blood vessel image. information acquisition apparatus according to claim Rukoto that Yusuke and fourth parts of selecting information. The fourth part is an evaluation obtained by using the index data, the pixel value of the plurality of first regions, the pixel value of the plurality of second regions, and the minimum value of the pixel value in the image data. The information acquisition device according to claim 1, wherein the selection is made based on a value. The information acquisition device according to claim 1 or 2, wherein the related information is a data set including information of image data acquired by the first part that generates the difference image data. Information acquiring apparatus according to any one of claims 1, characterized in that to have a pre-Eat flow change unit 3. The invention according to any one of claims 1 to 4 , wherein immediately after the operation of the blood flow changing portion is within 1 minute after the operation of the blood flow changing portion when the imaging site is a finger. Information acquisition device. Immediately after the operation of the blood flow change portion, when the imaging site is a finger, the blood flow is within the time required to propagate a distance corresponding to the thickness of the finger at a flow velocity of 0.3 mm / sec. The information acquisition device according to any one of claims 1 to 5, wherein the information acquisition device is characterized. It has a blood flow changing part that changes the blood flow of the blood vessel from the outside,
The first part acquires a plurality of image data including the imaged portion at different times in the operating state of the blood flow changing portion.
The second part uses the time when the time differential value of the pixel value fluctuation in the first region or the second region is larger than a predetermined threshold value as the blood flow fluctuation information, and is based on the blood flow fluctuation information. The information acquisition according to any one of claims 1 to 3, wherein the selected image data includes image data taken at a time when the time differential value of the pixel value fluctuation is larger than a predetermined threshold value. apparatus. 4. The operation of the blood flow changing portion is characterized in that the blood flow changing portion starts compression on a subject having an imaging site including the blood vessel or releases the compression on the subject. 7. The processing apparatus according to any one of 7. The third part is a pixel value when the first region and the second region are each composed of a single pixel, and the first region and the second region are each a plurality of pixels. Any one of claims 1 to 8 , characterized in that the average value or the maximum value or the minimum value of the pixel values of a plurality of pixels is acquired as the data to generate the index data in the case of being composed of The information acquisition device described in the section. The second region is a straight line having a direction substantially orthogonal to the axial direction of the blood vessel through which the first region is arranged and adjacent to the blood vessel in which the first region is arranged. The invention according to any one of claims 1 to 9, wherein the image is located between the blood vessel and the blood vessel and at the position closest to the first region where the pixel value is maximum or minimum. Information acquisition device. The second region is arranged at a predetermined distance from the first region on a straight line having a direction substantially orthogonal to the axial direction of the blood vessel through which the first region is arranged. The information acquisition device according to any one of claims 1 to 9, wherein the predetermined distance is determined based on the spread of a point image function based on the scattering coefficient of a living body. The information acquisition device according to any one of claims 1 to 11, wherein the first region is set in a joint. The information acquisition according to any one of claims 1 to 12, wherein the first region sets at least a part of a region corresponding to an artery or vein of a finger joint portion or a new blood vessel group. apparatus. In the plurality of image data of the difference image data, the third part acquires the data of the first region and the data of the second region, respectively, and takes the data between the two different image data. The index data according to claims 1 to 13, wherein the index data is generated by using the difference in the data in the first region and the difference in the data in the second region between two different image data. The information acquisition device according to any one item. The information acquisition device according to any one of claims 1 to 14, wherein a plurality of pairs of the first region and the second region are set. In the third part, the data of the plurality of first regions in one image data of the difference image data is α1, the data of the plurality of first regions in the other image data of the difference image data is α2, respectively. The data of the plurality of second regions in the one image data is β1, the data of the plurality of second regions in the other image data are β2, respectively, and k is a positive constant, and the first region and the second region are second. When the blood vessel image contrast specified by the combination of regions is C,
The fourth part is the blood vessel image contrast C of each set.
C = {(α1-k ・ α2)-(β1-k ・ β2)} / {(α1-k ・ α2) + (β1-k ・ β2)}
The information acquisition device according to claim 15, wherein the selection is made for the combination of the image data and k that maximizes the average value of. In the third part, the data of the plurality of first regions in one image data of the difference image data is α1, the data of the plurality of first regions in the other image data of the difference image data is α2, respectively. The data of the plurality of second regions in the one image data is β1, the data of the plurality of second regions in the other image data are β2, respectively, and k is a positive constant, and the first region and the second region are second. When the blood vessel image contrast specified by the combination of regions is C,
The fourth part is a set of blood vessel image contrast C with respect to a preset reference contrast value Ci.
C = {(α1-k ・ α2)-(β1-k ・ β2)} / {(α1-k ・ α2) + (β1-k ・ β2)}
The information acquisition device according to claim 15, wherein the selection is made for the combination of the image data and k that minimizes the standard deviation with respect to Ci. The information acquisition device according to any one of claims 1 to 17, wherein the first part generates processed image data using the plurality of image data. The information acquisition device according to claim 18, wherein the first part acquires image data generated by averaging image data having similar shooting conditions as the processed image data. The information acquisition device according to any one of claims 1 to 19, wherein the first part acquires image data in which a blood vessel portion is aligned with each image data. The second part according to any one of claims 1 to 20, wherein the difference image data which is the data of the difference between the coefficient multiple of one of the two image data and the other is generated. Information acquisition device. The invention according to any one of claims 1 to 21, wherein one region of the imaging site related to the blood flow fluctuation information is at least one of the first region and the second region. Information acquisition device. A step of attaching a blood flow changing portion for changing the blood flow of the imaging site to a subject including the imaging site, and
The first step of acquiring a plurality of image data including the imaged area in the imaged area by photographing at a plurality of times so that the blood flow of the imaged part is different .
Generating a difference processed difference of image data between different image data selected from a selected plurality of image data to include image data obtained in response to shooting time immediately after the operation of the blood flow changing portion The second step to do
In the difference image data and the plurality of image data, it is a part of a first region which is a part of a region corresponding to a blood vessel and a region other than a region adjacent to the first region and corresponding to the blood vessel. In the second area, the third step of acquiring index data using the data in, and
Based on the index data, from the difference image data and the image data group including the plurality of image data , the relationship between the image data including the contrast-enhanced blood vessel image or the image data including the contrast-enhanced blood vessel image. The fourth step of selecting information and
Information acquisition method according to claim Rukoto to have a. The information acquisition method according to claim 23, wherein a plurality of pairs of the first region and the second region are set. The information acquisition device according to claim 23 or 24, wherein one region of the imaging site related to the blood flow fluctuation information is at least one of the first region and the second region. The information acquisition method according to any one of claims 23 to 25, wherein the first step is terminated when the index data acquired in the third step satisfies a predetermined condition. The information acquisition method according to any one of claims 23 to 26, further comprising a fifth step of generating output data using the selected image data or related information. In the fourth step, after making the selection based on the index data,
26 or claim 26, wherein at least one of the first region and the second region is reset to different positions in the third step, and the selection is made again in the fourth step. The information acquisition method according to 27 . The information acquisition method according to any one of claims 23 to 28, which comprises a step of selecting a wavelength of light used for photographing. A light source that irradiates a subject including blood vessels with light,
A detection unit that is irradiated with light from the light source, detects light propagating through the subject, and generates a signal.
An information acquisition device that acquires information about blood vessels using signals from the detection unit, and
It is a photographing device having
An imaging device according to any one of claims 1 to 22, wherein the information acquisition device is the information acquisition device. The imaging device according to claim 30, wherein the light emitted from the light source to the subject is light in at least a part of the wavelength region from the visible to the near infrared band.

Images