JP2017000675A - Medical image processing apparatus and X-ray imaging apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a medical image processing apparatus and a medical imaging apparatus comprising it, with which accurate approximation of concentration and accurate approximation of image property may be executed between a plurality of images which should be compared.SOLUTION: A medical image processing apparatus comprises: an extracting part 41 which is an image processing part arranged on an image processing apparatus independent from a medical imaging apparatus or a medical image apparatus and which extracts image data in specific regions from an image obtained with the medical imaging apparatus; and an image property processing part 43 which executes process with respect to a plurality of images for uniforming properties defining images between the plurality of images based on image data in the regions respectively extracted by the extracting part. The image property processing part comprises a gradation conversion part 45 executing process with respect to the plurality of pieces of image data for uniforming gradation between the plurality of pieces of image data; and a frequency emphasis conversion part 49 executing process for uniforming frequency emphasis property between the plurality of pieces of image data.SELECTED DRAWING: Figure 12

Description

  The present invention relates to an apparatus for processing medical images, and more particularly to a technique for converting a plurality of images acquired under different models and different conditions into images that can be easily compared with each other.

  In the field of medical image diagnosis, for example, it is frequently performed to compare a plurality of images with different acquisition times for the same patient, observe changes, and compare an image to be diagnosed with a separately acquired reference image. Is called. In addition, with the replacement of the old and new imaging devices, there is a demand for matching the display conditions of images acquired by the new device with the conditions of the old device.

  However, if the model of the medical imaging device that acquired the multiple images to be compared is different, depending on the model, the imaging conditions and display conditions at the time of acquiring the image will differ, so that the image gradation, frequency enhancement level, etc. The characteristics may be different. In such a case, it is not possible to correctly compare whether the difference in the contrasted images is a difference due to the image characteristics, or a difference due to a change in the diagnosis site or lesion or an individual difference. In many cases, the conditions under which an image is captured are unknown, and in that case, the image cannot be corrected based on those conditions.

  As a technique that contributes to the comparison of images acquired by different models, Patent Document 1 discloses a technique that approximates the density distribution of a medical image to be compared to a predetermined reference. Specifically, with this technique, for each of a plurality of images, a histogram distribution is obtained for a specific region extracted from the images, and the density distribution of each image is normalized by matching the histogram peaks and average values. The method is adopted.

JP 2004-97331 A

  However, in the technique described in Patent Document 1, a predetermined region is extracted from the X-ray image, and the density distribution is normalized using a histogram created for the extracted region. Although the density of a plurality of images can be made uniform, the accuracy of density distribution normalization is deteriorated for portions other than the area. Further, it is not possible to reflect the difference in the structure of the subject and the thickness of each structure that differ from image to image only by aligning the histogram peaks and the like. For this reason, there is a possibility that high accuracy cannot be secured even for the extracted region.

  The present invention solves the above-described problems of the prior art, and includes a medical image processing apparatus capable of performing accurate density approximation and accurate image characteristic approximation between a plurality of images to be compared, and the same. Another object of the present invention is to provide a medical imaging apparatus.

The medical image processing apparatus of the present invention that solves the above problems includes an extraction unit that extracts image data of a specific region from an image acquired by the medical imaging device, and an image of the region extracted by the extraction unit for each of a plurality of images. An image characteristic processing unit that performs a process of aligning characteristics defining the image between the plurality of images based on the data.
The characteristics that define the image include gradation or frequency enhancement. In the former case, the image characteristic processing unit includes a gradation conversion unit that aligns gradations of the plurality of images between the plurality of images. In the latter case, a frequency enhancement conversion unit that performs a process of aligning the frequency enhancement for a plurality of images is provided. The image characteristic processing unit includes at least one of a gradation conversion unit and a frequency enhancement level conversion unit.

  According to the present invention, accurate density approximation can be performed by performing gradation conversion as image characteristic processing. Further, the accuracy of image characteristic approximation can be improved by performing frequency enhancement conversion.

The figure which shows the whole structure of the X-ray imaging device with which this invention is applied. Functional block diagram of the image processing unit of the first embodiment Flow showing operation of image processing unit of first embodiment (A), (b) is a figure explaining area extraction Flow showing details of steps S304 and S305 in FIG. (A), (b) is a figure which shows the example of a gradation conversion table, respectively. Functional block diagram of the image processing unit of the second embodiment Flow showing operation of image processing unit of second embodiment The figure explaining the extraction process in 2nd embodiment The figure explaining frequency emphasis conversion in a second embodiment (A), (b) is a figure which shows the example of a change of the extraction process in 2nd embodiment, respectively. Functional block diagram of the image processing unit in the third embodiment Flow showing operation of image processing unit in the fourth embodiment The figure explaining the image processing in 4th embodiment

  Hereinafter, embodiments of a medical image processing apparatus and a medical imaging apparatus of the present invention will be described with reference to the drawings.

  The medical image processing apparatus according to the present embodiment has a function of performing processing for matching image characteristics that define a plurality of images, and the plurality of images include, for example, images captured by different models, imaging Includes images with different times. Different models include the same type of modality (medical imaging apparatus) and different models and different modalities, for example, MRI apparatus and CT apparatus.

  The medical imaging apparatus according to the present embodiment includes an image processing unit that processes an image acquired by the medical imaging apparatus. The image processing unit has the function of the above-described medical image processing apparatus, that is, a function of performing processing for matching the image characteristics that define the plurality of images.

  Hereinafter, the medical image processing apparatus of the present embodiment will be described by taking the case where the medical imaging apparatus is an X-ray imaging apparatus as an example.

  As shown in FIG. 1, the X-ray imaging apparatus 100 includes an X-ray generation unit 10 that generates X-rays, and an X-ray detection unit 20 that detects X-rays emitted from the X-ray generation unit and transmitted through the inspection target 90. An image creation unit 30 that creates an X-ray image of the inspection object 90 based on the X-rays detected by the X-ray detection unit 20, and an image processing unit that performs image processing on the X-ray image created by the image creation unit 30 40, a control unit 50 that controls each element constituting the apparatus, and an image creation unit 30, an image processing unit 40, and a storage unit 60 that stores data and parameters necessary for the processing of the control unit 50. Yes.

  The X-ray imaging apparatus 100 further includes a display unit 70 that displays an image created by the image creation unit 30 and the image processing unit 40, and an operation unit for an operator to input commands and imaging conditions necessary for the operation of the device. 80. The display unit 70 and the operation unit 80 may be integrated into one console that includes the image creation unit 30, the image processing unit 40, the control unit 50, and the storage unit 60.

  Although not shown in FIG. 1, the X-ray generator 10 includes an X-ray tube and a high voltage generator that supplies a high voltage to the X-ray tube. In the vicinity of the X-ray tube, a diaphragm for limiting the X-ray irradiation range irradiated by the X-ray tube, a filter for controlling X-ray energy, and the like are arranged.

  The X-ray detection unit 20 includes an X-ray detector such as a flat panel detector (FPD) in which a plurality of X-ray detection elements are arranged in a two-dimensional direction, and is opposed to the X-ray tube with the inspection target 90 interposed therebetween. Placed in position. The X-ray detector outputs an electrical signal corresponding to the detected X-ray and sends it to the image creation unit 30. In addition to the X-ray detector, the X-ray detector 20 may be provided with a grid for preventing scattered X-rays from entering each X-ray detection element of the X-ray detector.

  The image creation unit 30 creates an image in accordance with preset input / output characteristics. The input / output characteristics determine the relationship of the image signal (output signal) output from the image creation unit 30 with respect to the signal (input signal) from the X-ray detection unit 20 input to the image creation unit 30. As a result, image characteristics such as density, gradation, contrast, and frequency enhancement degree of the image represented by the image signal are determined. In other words, the input / output characteristics are determined by setting these image characteristics, and the image characteristics set as default can be adjusted via the operation unit 80, and thus the input / output characteristics can be adjusted. Change.

  The image processing unit 40 extracts characteristics of the image created by the image creation unit 30 and the image read from the storage unit 60 or an external device, and defines the characteristics that define the image using the image data of the extracted region. Processing for adjustment, processing for displaying an image on the display unit 60, and the like are performed. In FIG. 1, the image processing unit 40 is illustrated as a component of the X-ray imaging apparatus 100, but may be an image processing apparatus independent of the X-ray imaging apparatus 100. The image processing apparatus is connected via a wired, wireless, portable recording medium, cloud, or the like. The specific configuration and processing contents of the image processing unit 40 (image processing apparatus) will be described later.

  The control unit 50 controls operations of the image creating unit 30 and the image processing unit 40 in addition to the above-described control of starting and stopping X-ray exposure by the X-ray generation unit 10. The functions of the control unit 50 and the image processing unit 40 can be realized by, for example, hardware such as a CPU or a processor having a calculation function and software (program) that defines the operation thereof. Some of them can also be realized by a processor, an electronic circuit (ASIC: application specific integrated circuit, an FPGA: field-programmable gate array), or the like.

  The configuration of the image processing unit 40 can take various forms depending on the characteristics of the image to be processed. Hereinafter, embodiments in which the form of the image processing unit 40 is different will be described. In the drawings showing the following embodiments, common elements are denoted by the same reference numerals, and redundant description is omitted.

<First embodiment>
The image processing unit 40 according to the present embodiment has a function of aligning gradations of a plurality of images. As illustrated in FIG. 2, an image created by the image creation unit 30 of the medical imaging apparatus or an image stored in the storage unit 60. The image reading unit 47 that captures an image from the image, the extraction unit (region of interest extraction unit) 41 that extracts image data of a specific region from the image captured by the image reading unit 47, and the extraction unit respectively extract a plurality of images. An image characteristic processing unit 43 that performs a process of aligning characteristics that define the entire image, that is, gradation, among a plurality of images based on the image data of the region. The image characteristic processing unit 43 includes a gradation conversion unit 45 that aligns the gradations of a plurality of images between the plurality of images. Specifically, the gradation conversion unit 45 creates a gradation conversion table 44 based on the image data of a plurality of areas extracted by the extraction unit, and based on the gradation conversion table 44, the gradation conversion table 44 stores a plurality of image levels. Align the key. The created gradation conversion table 44 may be recorded in the storage unit 60.

  The plurality of images handled by the image processing unit 40 of the present embodiment are, for example, two X-ray transmission images acquired by X-ray imaging devices of different models, and one of them is an X-ray imaging to which the image processing unit 40 belongs. An image created by the image creation unit 30 of the apparatus 100 (FIG. 1), and the other is an image captured by another X-ray imaging apparatus.

  Hereinafter, the operation of the image processing unit 40 of the present embodiment will be described with reference to the flow shown in FIG. The operation of the image processing unit 40 is mainly performed under the control of the control unit 50, but is performed according to the operation of the operator via the operation unit 70 as necessary.

  First, the image reading unit 47 captures an image A acquired by another X-ray imaging apparatus, such as an old X-ray imaging apparatus or an X-ray imaging apparatus of a different model, directly or indirectly via a recording medium ( S301). The image A read at the same time may be displayed on the display unit 90. Further, the image B to be compared with the image A is selected from the images acquired by the X-ray imaging apparatus 100 and stored in the storage unit 60 (S302).

  The selection of the image B is, for example, when both the images A and B are images described in the DICOM format and include additional information such as imaging conditions and subject information as data, based on the additional information. In addition, the image processing unit 40 (image reading unit 47) can automatically select. For example, an imaging technique (such as chest imaging or abdominal imaging) that is supplementary information of image data to be compared or a subject is compared, and a matching one is selected. Further, a plurality of images may be displayed on the display unit 90 to allow the operator to select arbitrary images.

  When selecting an image, if it is an X-ray image, the imaging conditions such as tube voltage (kV) and exposure dose (mAs) are compared, and the difference in imaging conditions is within a predetermined range, for example, within 50%. A thing is selected (S303). If the imaging conditions differ greatly, they are not selected because they are not suitable for comparison.

  If two images to be compared are determined, the extraction unit 41 extracts a plurality of regions for each image (S304). As a region extraction method, a known method disclosed in the above-mentioned Patent Document 1 can be employed. The case of the chest image shown in FIG. 4A will be briefly described as an example. For example, in the case of a lung field, since it is almost an air layer, the amount of X-ray transmission is much larger than other regions, and the signal value In the histogram showing the distribution of, the region is distinguished from other regions by a clear value, so the lung field region is extracted by extracting the region whose signal value is higher than that value (or vice versa in the case of a black and white inverted image) 401 can be extracted. A region between the left and right lung field regions 401 can be extracted as a spine region 403. Further, the diaphragm region 405 is extracted as a diaphragm region 405 from a boundary (x, y) of the end of the lung field region 401 to a predetermined distance S (x). A region surrounded by the spine region 403, the diaphragm region 405, and the left lung field region 401 is extracted as a heart region 407.

  Next, a gradation conversion table is created using the pixel values (signal values) of a plurality of extracted regions (S305). The operation from the extraction of each region to the creation of the gradation conversion table for the chest image will be described in detail with reference to the flow of FIG.

  As shown in FIG. 4A, in the image to be processed, in addition to the image of the subject (subject region 400), the portion 410 where the X-ray is not irradiated by the diaphragm and the direct X-ray where the subject does not exist are included. Region 420 exists. The pixel values in these areas 410 and 420 are reference values that are the upper and lower limits of the pixel values of the entire image. Therefore, prior to extracting each region from the subject region 400, the aperture region 410 and the straight X-ray region 420 are extracted (S501, S502), and their pixel values are determined. Further, by removing these areas 410 and 420, the subject area 400 is automatically extracted.

  Next, a region of interest, in this example, a lung field region 401, a diaphragm region 405, and a heart region 407 are extracted from the subject region 400 (S503). The extraction method is as described above. Then, feature amounts such as the maximum value, the minimum value, and the average value of the pixel values are calculated for the extracted region (S504). In this embodiment, as shown in FIG. 6B, the average value of the pixel values of each region is obtained as the feature amount, and the maximum value is also calculated for the lung field region. The above processing is performed for both of the two images A and B which are comparison targets.

  Next, for the two images, a graph indicating the correspondence between the obtained feature quantities of the respective regions, that is, the gradation conversion table 46 is created (S505). An example of the gradation conversion table 46 represented by a graph is shown in FIG. The vertical axis of this graph represents the pixel value (feature amount) of the image B, and the horizontal axis represents the pixel value (feature amount) of the image A. This graph is a curve obtained by interpolating the values between them by a process such as moving average processing and fitting based on a table having discrete values as shown in FIG. If the gradations of the two images A and B match, the curve of the graph becomes a straight line (indicated by a dotted line). For example, each image creation of the imaging device that acquired the image B and the imaging device that acquired the image A When there is a difference in gradation due to a difference in input / output characteristics in the part, it does not become a straight line as shown in the figure.

  The gradation converting unit 45 performs processing for converting, for example, the gradation of the image A into the gradation of the image B using the gradation conversion table 46 (FIG. 3: S306). This process is a process for replacing the value of each pixel of the image A with the value of the corresponding pixel of the image B according to the gradation conversion table 46. The reverse is also possible (B ← A). Two images with the same gradation may be displayed on the display unit 70 for comparison.

  According to the present embodiment, it is possible to perform accurate density approximation by creating a gradation conversion table for two images to be compared and by aligning gradations using this gradation conversion table. Accuracy can be increased. Since the created gradation conversion table has a property close to the conversion table between the input / output characteristics of the medical imaging apparatus that acquired the image A and the input / output characteristics of the medical imaging apparatus that acquired the image B, Not only the images A and B used for the creation, but also a general application can be made when comparing images obtained by two medical imaging devices.

<Second embodiment>
The image processing unit 40 of the present embodiment is characterized in that it has a function of aligning frequency enhancement levels as image characteristics for a plurality of images.

  That is, as shown in FIG. 7, the image processing unit 40 of the present embodiment includes a frequency enhancement degree conversion unit 49 that performs a process of aligning the frequency enhancement degree for a plurality of images. The provision of the image reading unit 47 and the extraction unit 41 is the same as in the first embodiment. Hereinafter, the image processing unit 40 of the present embodiment will be described focusing on the function of the frequency enhancement conversion unit 49.

In general, image data consists of a plurality of spatial frequency components. Frequency components can be broadly classified into super-high frequency components, high-frequency components, medium-frequency components, and low-frequency components, each reflecting the definition of the structure included in the image. Taking a chest image as an example, the superhigh frequency component is the trabecular bone, the high frequency component is the blood vessel, the medium frequency component is the bone side of the thoracic vertebra, and the low frequency component is the signal component of the entire image. The frequency enhancement degree is a degree at the time of performing edge enhancement of a specific frequency component, for example, a trabecular bone or a blood vessel, in the image, and is expressed by α _n in Expression (1). n is an integer of 1 to N, where the number of frequency components is N (hereinafter the same).
[Equation 1]
Output image = input image + Σα _n × frequency component Fn (1)

In a medical imaging apparatus such as an X-ray imaging apparatus, a desired edge-enhanced image (output image) is obtained by the operator changing the value of α _n multiplied by the frequency component in Equation (1). Can do. Each frequency component in equation (1) can be extracted from the input image by applying a predetermined frequency filter to the input image.

  When comparing a plurality of images (output images) captured by different models, accurate comparison cannot be performed if their frequency enhancement levels are different. Further, since the frequency enhancement level cannot be derived directly from the output image, it is not possible to correct the frequency enhancement level to make the frequency enhancement levels of a plurality of images uniform. For this reason, the frequency enhancement degree conversion unit 49 of the present embodiment calculates a profile of a predetermined part for each of a plurality of images, and performs a process of aligning the frequency enhancement degree by comparing the amplitudes.

  Hereinafter, the function of the frequency enhancement degree conversion unit 49 will be described in detail together with the processing procedure of the image processing unit 40 shown in FIG. Here, a plurality of images to be compared will be described by taking a chest X-ray image acquired by an X-ray imaging apparatus as an example. In FIG. 8, steps that perform the same processing as the steps shown in FIG. 3 are denoted by the same reference numerals, and redundant description is omitted.

  First, the image reading unit 47 reads an image and selects two images to be compared (S301, S302). These images may be stored in the storage unit 60 or an external storage device, or may be directly output from the image creation unit 30. Next, the imaging conditions (tube voltage and exposure dose) are compared based on the incidental information included in the image data, and it is confirmed whether the difference in imaging conditions is within a predetermined range (S303).

  Next, the extraction unit 41 extracts a region reflecting the frequency component of interest from the two images (S310). The region to be extracted may be designated by the operator via the operation unit 70 or may be automatically performed. As an example of performing automatically, for example, a method of extracting a plurality of regions (lung field, thoracic vertebrae, diaphragm) and the like and extracting a region having the largest difference in pixel values (for example, average value) between the two images There is. The method for extracting the region is the same as in the first embodiment. FIG. 9 shows the thoracic vertebra as an example of the region extracted by the extraction unit 41 for frequency enhancement conversion. As described above, in the thoracic spine image, the signal component of the medium frequency component is dominant, and when the enhancement degree of the medium frequency component is set to be relatively high, the pixel value is relatively high, If the value is set low, the pixel value becomes relatively low.

The frequency enhancement degree conversion unit 49 performs image analysis on the extracted region, here, the image of the thoracic vertebra, and calculates a correction amount for aligning one image with the other image (S311). Specifically, a thoracic vertebra having relatively few signal components other than the medium frequency component is selected from the extracted thoracic vertebra image, and its profile is calculated. FIG. 9 shows a state where three of the 10 vertebrae that are close to the heart and 9 to 11 vertebrae are selected. FIG. 10 shows three vertebra profiles calculated for the two images. When the amplitudes of the profiles of the two images are compared, the image B is larger than the image A (P _A <P _B ). The frequency enhancement level conversion unit 49 obtains the amplitude ratio (P _B / P _A or P _A / P _B ) of the profile as a correction value, and uses this correction value to determine the enhancement level of one of the images. Correction to match the degree of enhancement is performed (S312).

If the image B is an image acquired by the X-ray imaging apparatus 100 including the image processing unit 40, the image A is an image acquired by another X-ray imaging apparatus (old apparatus), and the frequency enhancement degree is unknown. , The enhancement degree α _B of the medium frequency component set in the X-ray imaging apparatus 100 is converted by the following expression (2), whereby the enhancement degree of the intermediate frequency component of the image B is changed to the intermediate frequency of the image A. It is possible to align with the degree of emphasis of the component.

[Equation 2]
Enhancement degree after conversion = α _B × (P _A / P _B ) (2)

Even if the frequency enhancement degree of both the image A and the image B is unknown, the predetermined frequency component of both images can be obtained by performing correction according to the following equation (3) on one image (for example, the image B). The degree of emphasis can be made uniform.
[Equation 3]
Corrected image = original image + frequency component × (P _A / P _B ) (3)

  9 shows an example in which the extraction unit 41 extracts the thoracic vertebra region of the chest X image, but as shown in FIGS. 11 (a) and 11 (b), the thoracic vertebrae is used instead of or in addition to the thoracic vertebra. Or a rib may be extracted and a partial profile of the extracted image may be obtained. When there are a plurality of extracted regions and the enhancement degree of the same frequency component is to be corrected, a plurality of correction values may be obtained and the average value may be used in the correction process (S312). As a result, the correction accuracy can be increased.

  In addition, when it is desired to align the frequency enhancement degree with a plurality of images to be compared with respect to two or more frequency components, a region (for example, a thoracic vertebra region and a trabecular region) reflecting each frequency component is selected and selected for each. If the profile of the image is calculated and the ratio of the amplitudes is obtained, the frequency enhancement degree can be corrected (converted) in the same manner as described above.

  According to the present embodiment, even if the frequency enhancement degrees of a plurality of images to be compared are unknown, both can be matched, and an accurate comparison of images of frequency components to be observed can be performed.

<Third embodiment>
In the first and second embodiments, the case of performing gradation conversion or frequency enhancement degree conversion alone has been described. However, the second embodiment and the first embodiment can be combined. That is, for each of a plurality of images, a plurality of regions are extracted, and a gradation conversion table (FIG. 6A) is created using their pixel values (average value and maximum value). After aligning the gradations, processing for correcting the frequency enhancement degree based on the second embodiment is performed for a predetermined region, or conversely, for a plurality of images, the frequency enhancement degree is aligned for a predetermined frequency component, and then the first It is possible to perform gradation conversion based on the embodiment.

  FIG. 12 shows a functional block diagram of the image processing unit 40 in that case. As shown in the figure, the image characteristic processing unit 43 of the present embodiment aligns the frequency emphasis levels of the plurality of image data with the gradation conversion unit 45 that aligns the gradations of the plurality of image data among the plurality of image data. A frequency enhancement degree conversion unit 49 that performs processing is provided. Other configurations are the same as those in the first and second embodiments. The functions of the tone conversion unit and the frequency enhancement conversion unit are as described in the first embodiment and the second embodiment, respectively.

  According to the present embodiment, the degree of coincidence of image characteristics of images to be compared can be further increased by performing two processes of gradation conversion and frequency intensity conversion.

<Fourth embodiment>
The image processing unit of the present embodiment also performs the frequency intensity conversion process in the same manner as in the second embodiment. However, the present embodiment does not align the image characteristics of the actual image of the subject but uses different imaging devices ( For example, an image of a simulated body is used to align image characteristics of images acquired by an old X-ray imaging apparatus and a new X-ray imaging apparatus. From the image of the simulated body, the difference in the image characteristics of the images acquired by the two imaging devices is estimated, and using the difference in the image characteristics, the image characteristics of the image subsequently acquired by one imaging device (new device) Align with the image characteristics of (old device).

  Since the configuration of the image processing unit in this embodiment is the same as that of the image processing unit shown in FIG. 7 or FIG. 12, the following description will be described with the aid of these drawings as necessary.

  In the present embodiment, the simulated body is not particularly limited as long as it has a predetermined frequency component, and for example, a grid, a resolution chart, a phantom, or the like provided in the X-ray detection unit 20 of the X-ray imaging apparatus is used. There are various frequency patterns in the resolution chart, and a desired frequency pattern can be used. As the phantom, for example, a desired phantom such as a lumbar phantom or a thoracic phantom can be selected and used.

  A processing flow of the image processing unit of the present embodiment will be described with reference to FIG. Here, a case where the image characteristic (frequency enhancement degree) of the new apparatus is made to match the image characteristic of the image obtained by the old apparatus will be described as an example.

  First, a simulated body, for example, a grid is imaged by the old apparatus and the new apparatus, and an image is obtained (S320). Note that the grid spacing (frequency) is the same for both devices. FIG. 14 shows an example of an image when the grid is imaged. In FIG. 14, the left side is an image of the old device, and the right side is an image of the new device, showing three examples. As shown in the figure, the grid image is a thin striped image having a frequency component of the same period as the strip along the strip array direction. A profile of the image in a direction orthogonal to the stripe arrangement direction (frequency component direction) is calculated, and the amplitude is obtained (S321).

When the obtained amplitude is the same in the grid image of the old device and the grid image of the new device (the center on the right side in FIG. 14), the frequency emphasis degree of both of the frequency components F _n of the grid is the same, so the correction is performed. unnecessary. If the amplitude of the old device is greater than the amplitude of the new device (the right side in FIG. 14), to increase the enhancement degree of the frequency component F _n of the new device, if the amplitude of the former device is smaller than the amplitude of the new apparatus (right side under Fig. 14), to reduce the enhancement degree of the frequency component F _n of the new apparatus. Specifically, an amplitude ratio R _n (the amplitude of the old device = the amplitude of the new device) is obtained as a correction value (S322), and this correction value R _n is used as the enhancement degree α _n of the frequency component F _n of the new device. Multiply (S323).

As simulant, in the case of using a resolution chart of a frequency pattern of a plurality of frequency components F ₁ to F _N, the correction value R ₁ to R _N is obtained for each frequency component, correcting the respective frequency enhancement degree Can do.
Although the frequency emphasis is given as an example of the image characteristic to be converted in the present embodiment, the same applies to the gradation.

  According to this embodiment, when an image is acquired by a certain medical imaging device, the image characteristics of the medical imaging device can be aligned with the image characteristics of another imaging device that acquired a past image. An image having the same image characteristics as the past image can be obtained, and an accurate comparison between the past and current images can be performed.

  According to the present invention, an image acquired by an old device and an image acquired by a new device, a past image and a current image, a plurality of images acquired by devices of different models, a plurality of images acquired by devices of different modalities, etc. When comparing images, a technique capable of performing accurate comparison is provided because the characteristics of images to be compared are uniform.

DESCRIPTION OF SYMBOLS 10 ... X-ray generation part, 20 ... X-ray detection part, 30 ... Image preparation part, 40 ... Image processing part, 41 ... Extraction part, 43 ... Image characteristic processing part, 45 ... gradation conversion unit, 46 ... gradation conversion table, 47 ... image reading unit, 49 ... frequency enhancement degree conversion unit, 50 ... control unit, 60 ... storage unit, DESCRIPTION OF SYMBOLS 70 ... Display part, 80 ... Operation part, 90 ... Subject, 100 ... X-ray imaging device (medical imaging device).

Claims (10)

An extraction unit that extracts image data of a specific area from an image acquired by the medical imaging apparatus;
For a plurality of images, processing for aligning the characteristics defining the image and including the gradation or frequency enhancement level between the plurality of images based on the image data of the regions extracted by the extraction unit. A medical image processing apparatus comprising: an image characteristic processing unit that performs the processing. The medical image processing apparatus according to claim 1,
The medical image processing apparatus, wherein the image characteristic processing unit includes a gradation conversion unit that aligns gradations of the plurality of images between the plurality of images. The medical image processing apparatus according to claim 2,
The gradation conversion unit creates a gradation conversion table based on the image data of the plurality of regions extracted by the extraction unit, and aligns the gradations of the plurality of images based on the gradation conversion table. A medical image processing apparatus. The medical image processing apparatus according to claim 1,
The medical image processing apparatus, wherein the image characteristic processing unit includes a frequency enhancement degree conversion unit that performs a process of aligning the frequency enhancement degree for the plurality of images. The medical image processing apparatus according to claim 4,
The image data of the area extracted by the extraction unit is image data having spatial frequency characteristics in a predetermined direction,
The frequency enhancement degree conversion unit calculates a profile in a direction orthogonal to the predetermined direction for the image data of the region extracted by the extraction unit, calculates an amplitude of the profile, and based on the amplitude of the profile, A medical image processing apparatus characterized by aligning frequency enhancement levels between a plurality of images. The medical image processing apparatus according to claim 4,
The plurality of images are images of a simulated body having spatial frequency characteristics in a predetermined direction, and the frequency enhancement degree conversion unit is an area extracted from the simulated body image or the image of the simulated body by the extraction unit. A profile is calculated in a direction orthogonal to the predetermined direction and the amplitude of the profile is calculated, and the frequency enhancement level is aligned between the plurality of images based on the amplitude of the profile. Medical image processing apparatus. The medical image processing apparatus according to any one of claims 1 to 6,
The medical image processing device, wherein the plurality of images are images acquired by different medical imaging devices. The medical image processing apparatus according to claim 1,
The image characteristic processing unit, for the plurality of image data, a gradation conversion unit that performs a process of aligning gradations between the plurality of image data, and a frequency that performs a process of aligning frequency enhancement between the plurality of image data A medical image processing apparatus comprising: an enhancement degree conversion unit.   The medical image processing apparatus according to any one of claims 1 to 8, wherein the medical imaging apparatus is an X-ray imaging apparatus. Based on the X-ray generation unit that generates X-rays, the X-ray detection unit that detects X-rays emitted from the X-ray generation unit and transmitted through the inspection object, and the X-rays detected by the X-ray detection unit An image creation unit that creates an X-ray image to be inspected, and an image processing unit that performs image processing on the X-ray image created by the image creation unit;
The image processing unit includes: an extraction unit that extracts specific regions for the first X-ray image created by the image creation unit and a second X-ray image different from the X-ray image; and the extraction unit Based on the image data of the extracted region, the characteristic that defines the first X-ray image and includes the gradation or the frequency enhancement degree is changed to the characteristic that defines the second X-ray image. An X-ray imaging apparatus comprising: an image characteristic processing unit that performs an aligning process.