JPWO2015174206A1 - Image diagnostic apparatus and gradation information setting method - Google Patents

Abstract

In order to provide an image diagnosis apparatus and a gradation information setting method capable of displaying a desired region with a desired contrast and density while maintaining the amount of image information, the image processing apparatus 12 of the image diagnosis apparatus 1 includes: Calculate a histogram related to pixel values for a subject area image obtained by extracting the subject area from the image to be processed, calculate the separation points of the subject composition based on the characteristics of the histogram shape (mode and slope), and calculate the separation The pixel value corresponding to the point is included in the control point of the γ curve, which is the gradation information, and the boundary (separation point) between the low density area and the high density area of the subject is thus obtained based on the pixel value histogram of the image. Since the separation point is used as a control point, it is possible to give a desired contrast to a desired region of the subject region.

Description

  The present invention relates to an image diagnostic apparatus and a gradation information setting method, and more particularly to a gradation information setting technique for displaying a radiographic image with an appropriate density value and contrast.

  2. Description of the Related Art Conventionally, an apparatus that irradiates an object with radiation such as X-rays, detects an intensity distribution of the radiation transmitted through the object, and obtains a radiation image of the object is used. As a general method for such photographing, there is a film / screen method for X-rays. In recent years, with the advancement of digital technology, a technique has been proposed in which a radiographic image is converted into an electrical signal, the electrical signal is subjected to image processing, and then displayed as a visible image on a display or the like to obtain a high-quality radiographic image. . With the progress of semiconductor process technology, an apparatus for taking a radiographic image using a flat detector has been developed. These devices have a very wide dynamic range as compared with conventional radiation devices using a photosensitive film, and are practical in that a radiation image that is not affected by fluctuations in the amount of exposure of radiation can be obtained. Has advantages.

  The digital image data generated by such a flat panel detector is subjected to density normalization processing, frequency processing, and the like for each photographing, and is recorded in an image memory. When the recorded image is displayed on the display medium, a curve called display γ (hereinafter referred to as γ curve) necessary for the gradation conversion process is created by the image processing apparatus. The obtained γ curve is set in a look-up table (hereinafter referred to as LUT) that performs gradation conversion, and image data subjected to gradation conversion by the LUT is displayed on the display device. As described above, when display gradation conversion is performed, a γ curve is created to adjust the contrast and density of the entire image. For example, Patent Document 1 describes that a histogram relating to the density value of an image is created and the shape of the γ curve is adjusted using the minimum and maximum values as control points.

Japanese Unexamined Patent Publication No. 6-13520

  However, since the method of Patent Document 1 uses the minimum and maximum values of the histogram of density values as control points, it is possible to adjust the contrast and density of the entire image, but for density adjustment of a specific region of interest. Not suitable. Depending on the surgeon, there is a demand to display only the most desired region (region of interest) with optimal contrast. On the other hand, if a γ curve is created by focusing only on the region of interest, white crushing (low density side) or black crushing (high density side) may occur in a region other than the region of interest. This is not preferable because the information amount of the entire image is reduced.

  The present invention has been made in view of the above-described problems, and an object of the present invention is to provide an image diagnosis capable of displaying a desired region with a desired contrast and density while maintaining the amount of image information. An apparatus and a gradation information setting method are provided.

  In order to achieve the above-described object, the present invention provides an X-ray source that irradiates a subject with X-rays, an X-ray detector that is disposed opposite to the X-ray source and detects transmitted X-rays of the subject, and the X-rays An image processing device that generates image data based on transmitted X-rays output from a detector, a storage device that stores image data generated by the image processing device, and image data to be processed from the storage device Obtained and extracted by a subject region extraction unit that extracts a subject region from the acquired image data, a histogram calculation unit that calculates a histogram regarding pixel values of a subject region image obtained by the subject region extraction unit, and a calculation by the histogram calculation unit A separation point calculation unit for calculating a separation point of the subject composition based on the histogram, and gradation information for displaying the image data using the separation point as a control point. A gradation setting section, and a display control section that performs gradation conversion on the image data to be processed based on the gradation information set by the gradation setting section and displays the image data on a display device. The diagnostic imaging apparatus.

  In addition, the image processing device acquires transmitted X-rays of a subject, generates image data based on the acquired transmitted X-rays, and stores the image data in a storage device, and the image processing device stores image data to be processed. A step of extracting from the storage device and extracting a subject area from the acquired image data, a step of calculating an image processing device by the image processing device to calculate a pixel value of the subject region image from which the subject region has been extracted; Calculating a separation point of the subject composition based on the histogram, a step in which the image processing apparatus sets gradation information when displaying the image data with the separation point as a control point, and an image processing apparatus Gradation conversion of the image data to be processed based on the gradation information and displaying it on a display device. Setup is a method.

  According to the present invention, it is possible to provide an image diagnostic apparatus and a gradation information setting method capable of displaying a desired region with a desired contrast and density while maintaining an information amount of an image.

1 is an overall configuration diagram of a diagnostic imaging apparatus 1 according to the present invention. Flow chart showing the overall flow of X-ray image display processing Flow chart showing the procedure of display gradation processing Flow chart showing the procedure of subject area extraction processing The figure which shows the example of the image used in each step of an X-ray aperture removal process. (a) An example of a high-frequency component image 30, (b) An example of an image 31 in which a straight line is detected by Hough transform, (c) An example of an image from which an X-ray aperture is removed (X-ray aperture removed image 32) The figure which shows the example of the image used in each step of a direct X-ray area | region extraction process. (a) Example of X-ray aperture removed image 32, (b) Example of histogram 6 of X-ray aperture removed image 32, (c) Example of high-luminance region removed image 33 Flow chart showing the procedure of metal removal process (a) Example of high-frequency image 35, (b) Image 36 in which metal region is extracted by expansion processing after removing noise from high-frequency image 35 Flow chart showing the procedure of separation point calculation processing (a) Chest subject region image (chest image) 37 example, (b) Histogram 61 of chest image 37 in (a) (a) Example of bone region subject region image (bone image) 38, (b) Histogram 62 of bone image 38 in (a) Setting example of γ curve 71 based on histogram 61 Example of setting γ curve 72 based on histogram 62 Example of operation screen 8 which is a user interface

  An image diagnostic apparatus according to the present invention includes an X-ray source that irradiates a subject with X-rays, an X-ray detector that is disposed opposite to the X-ray source and detects transmitted X-rays of the subject, and the X-ray detector An image processing device that generates image data based on transmitted X-rays that are output, a storage device that stores image data generated by the image processing device, and image data to be processed are acquired from the storage device, A subject region extraction unit that extracts a subject region from the acquired image data, a histogram calculation unit that calculates a histogram relating to pixel values of a subject region image obtained by the subject region extraction unit, and a histogram calculated by the histogram calculation unit A separation point calculation unit for calculating a separation point of the subject composition based on the image, and a gradation setting for setting gradation information when displaying the image data using the separation point as a control point And a display control unit for converting the gradation of the image data to be processed based on the gradation information set by the gradation setting unit and displaying the converted image data on a display device.

  The separation point calculation unit is configured to calculate the separation point based on the slope and the mode of the histogram.

  Further, the separation point calculation unit obtains a mode point of the histogram, and a slope start point which is an absolute value of a slope between the mode point and the start point of the histogram, and a slope between the mode point and the end point of the histogram. The slope end point, which is an absolute value of each, is obtained, the slope start point is compared with the slope end point, and if the slope end point is greater, the slope of the histogram at each point between the slope start point and the mode point The separation point is the point having the smallest value among the absolute values of the slopes, and when the slope start point is larger, the absolute value of the histogram slope at each point between the mode point and the slope end point is the largest. A point having a small value is defined as a separation point.

  In addition to the separation point, the gradation setting unit further sets the gradation information using the start point and end point of the histogram as control points.

  The gradation setting unit further sets the gradation information using the bit minimum value and the bit maximum value as control points.

  The gradation setting unit sets the gradation information so as to form a curve by approximate interpolation.

  The image processing apparatus further includes a metal removal processing unit that removes a metal region from the subject region, and the histogram calculation unit calculates the histogram for the subject region image from which the metal region has been removed by the metal removal processing unit.

  The metal removal processing unit includes a process of determining whether or not the metal is a metal based on a standard deviation of density values of each region included in the image data.

  In addition, a user interface for displaying the γ curve as the gradation information and an operation unit for changing the position of the control point in the γ curve is further provided.

  In the gradation information setting method according to the present invention, an image processing device acquires transmitted X-rays of a subject, generates image data based on the acquired transmitted X-rays, and stores the image data in a storage device; Acquiring image data to be processed from the storage device, extracting a subject area from the acquired image data, and the image processing apparatus includes a histogram relating to pixel values of a subject area image from which the subject area has been extracted. A step of calculating, a step in which the image processing device calculates a separation point of the subject composition based on the histogram, and gradation information when the image processing device displays the image data with the separation point as a control point. Setting, and a step in which the image processing apparatus performs gradation conversion on the image data to be processed based on the gradation information and displays the image data on a display device. No.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

  First, the overall configuration of the diagnostic imaging apparatus 1 will be described with reference to FIG.

  The diagnostic imaging apparatus 1 according to the present invention is a general X-ray imaging apparatus that shoots an X-ray image that is a still image by irradiating a subject with X-rays, and an X-ray fluoroscopic imaging apparatus that obtains a moving image. Applicable. In the following description, a general X-ray imaging apparatus will be described as an example of the image diagnostic apparatus 1 according to the present invention.

  As shown in FIG. 1, the diagnostic imaging apparatus 1 controls an imaging system having an X-ray source 2 and an X-ray detector 5 disposed opposite to the X-ray source 2 via a subject 3, and controls the imaging system. A console 10 that performs processing such as image creation and display based on transmission X-ray data acquired in the system, and a top board 4 on which a subject is placed are provided.

  The X-ray source 2 includes an X-ray tube, a high voltage generator, and an X-ray diaphragm 2b. The X-ray source 2 is supplied with power from the high voltage generator and generates a predetermined dose of X-rays from the X-ray tube. The operation of the X-ray source 2 is controlled according to an X-ray control signal transmitted from the control device 11. The X-ray diaphragm 2b has a plurality of X-ray shielding plates that shield X-rays generated from the X-ray tube. The X-ray diaphragm 2b forms an X-ray irradiation region by moving a plurality of X-ray shielding plates according to a control signal from the control device 11.

  The X-ray detector 5 is a flat panel detector (FPD), an image intensifier (I.I) or the like, detects X-rays emitted from the X-ray source 2 and transmitted through the subject 3, and the X-ray intensity thereof. The electric signal corresponding to is output to the image processing device 12 of the console 4.

  The console 10 includes a control device 11, an image processing device 12, a storage device 13, a display device 14, and an input device 15.

  The control device 11 includes a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and the like. The control device 11 controls the operation of X-ray irradiation based on the input signal input from the input device 15, detects X-rays transmitted through the subject 3 (hereinafter abbreviated as “transmitted X-ray”), and collects data. Control of the operation, control of the movement operation of the position of the top 4 or the position of the X-ray source 2 are performed.

  The image processing device 12 acquires an electrical signal (transmitted X-ray data) corresponding to the transmitted X-ray transmitted from the X-ray detector 5. The image processing device 12 generates an X-ray image of the subject 3 based on the acquired transmission X-ray data, and stores it in the storage device 13.

  Further, the image processing apparatus 12 executes a gradation information setting process that is a process for adjusting the display state of the generated X-ray image (hereinafter simply referred to as “image”). Details of the gradation information setting process will be described later.

  The storage device 13 stores transmission X-ray data (low data) obtained by imaging, an image generated by the image processing device 12, or a diagnostic image generated at a gradation set in gradation information setting processing described later. Remember. Further, the storage device 13 stores a program relating to photographing operation / perspective operation, various photographing conditions, a program and data necessary for gradation information setting processing described later, and the like.

  The display device 14 includes a CRT, a liquid crystal panel, and the like, and displays an image generated by the image processing device 12, a diagnostic image, display data input from the control device 11, and the like.

  The input device 15 is an input device such as a keyboard and a mouse, for example, and inputs various instructions and information input by an operator. The operator performs operations interactively using external devices such as the display device 14 and the input device 15. The input device 15 may be a touch panel configured integrally with the display screen of the display device 14.

  Next, the functional configuration of the diagnostic imaging apparatus 1 will be described.

  As shown in FIG. 1, the diagnostic imaging apparatus 1 includes an image generation unit 20, an image data acquisition unit 21, a subject area extraction unit 22, a histogram calculation unit 23, a separation point calculation unit 24, gradations, as a functional configuration related to gradation settings. A setting unit 25 and a display control unit 26 are included. These units may be provided as functions of the image processing device 12 as shown in FIG. 1, or a part or all of them may be provided in the control device 11.

  The image generation unit 20 generates an X-ray image of the subject 3 based on the transmitted X-ray data sent from the X-ray detector 5. The generated image is stored in the storage device 13.

  The image data acquisition unit 21 acquires an image to be processed from the storage device 13.

  The subject region extraction unit 22 extracts a subject region from the image data acquired by the image data acquisition unit 21, and creates a subject region image. For example, the subject region extraction unit 22 extracts and removes the X-ray aperture region and the X-ray region directly from the image data. Further, a metal region included in the subject region is detected and removed to create a subject region image. Details of the X-ray aperture extraction processing, direct X-ray region extraction processing, and metal removal processing will be described later.

  The histogram calculation unit 23 calculates a histogram related to the pixel value of the subject area image created by the subject area extraction unit 22. The histogram relating to pixel values is data in which the horizontal axis represents pixel values and the vertical axis represents frequency. Hereinafter, a histogram relating to pixel values is simply referred to as a histogram. The histogram calculator 23 notifies the separation point calculator 24 of the calculated histogram.

  The separation point calculation unit 24 calculates the separation point of the subject composition based on the histogram calculated by the histogram calculation unit 23. The separation point of the subject composition is a representative pixel value for distinguishing different tissues on the image, such as a bone and skin, a lung field and a mediastinum, or the like. Details of the separation point calculation will be described later.

  The gradation setting unit 25 sets gradation information by including the separation point calculated by the separation point calculation unit 24 as a control point. The gradation information is specifically called a γ curve necessary for gradation conversion of image data. The γ curve is a curve that defines an output pixel value with respect to an input pixel value. The γ curve is set in a lookup table (hereinafter referred to as LUT) that performs gradation conversion.

  The display control unit 26 displays the image data subjected to gradation conversion by the LUT on the display device 14.

  Next, the gradation information setting process executed by the image processing apparatus 12 will be described with reference to FIG.

  The image processing device 12 performs basic correction processing (dark current correction, sensitivity correction, defect correction) on the image data generated from the transmitted X-ray data acquired from the X-ray detector 5 (step S101). . Further, after performing density normalization processing (step S102) for normalizing the density value of image data, frequency processing (step S103) for performing compression and enhancement processing for each image frequency, display gradation processing is executed. (Step S104).

  The display gradation processing in step S104 will be described with reference to FIG.

  In the display gradation process, the image processing device 12 extracts a subject area from the image data to be processed (step S201). In the subject area extraction process in step S201, the image processing apparatus 12 extracts and removes the X-ray aperture area and the direct X-ray area from the image.

  FIG. 4 shows an example of the procedure for subject area extraction processing. As shown in FIG. 4, the image processing apparatus 12 first extracts an X-ray aperture region from the image. The image processing device 12 creates a high-frequency component image 30 of the image (step S301; see FIG. 5 (a)), and performs a Hough transform (linear voting) on the direction of the diaphragm side based on the high-frequency component image 30. A straight line candidate is detected (step S302; FIG. 5 (b)). Further, the image processing apparatus 12 determines whether the line candidate is an object in the subject 3 or an area indicating the X-ray aperture 2b on the condition that the line candidate is located outside the line candidate obtained in step S302 (step S302). S303). The black frame region of the image 32 shown in FIG. 5 (c) is a region removed from the image 30 as an X-ray aperture region.

  Next, the image processing apparatus 12 directly extracts an X-ray region. First, the image processing apparatus 12 creates an image 32 obtained by removing the X-ray aperture region from the image 30 to be processed by the processing of Step S301 to Step S303 (Step S304; FIG. 6 (a)). The image processing apparatus 12 calculates a histogram 6 relating to pixel values for the image 32 from which the X-ray aperture region has been removed (step S305; see FIG. 6 (b)). Based on the histogram 6 calculated in step S305, the image processing device 12 performs threshold determination processing using a predetermined luminance value as a threshold (step S306), and removes the high luminance value region (step S307). By the processing from step S304 to step S307, an area such as air outside the subject area is removed as in the image 33 shown in FIG. 6C, and only the subject area remains.

  Returning to the description of FIG.

  When the subject region is extracted from the image 30 to be processed by the process of step S201, the image processing apparatus 12 determines whether or not the extracted subject region includes metal (step S202). If metal is included (step S202; Yes), a metal removal process is executed (step S203).

  The metal removal process in step S203 will be described with reference to FIGS.

  The image processing apparatus 12 creates a subject area image 33 obtained by removing the X-ray aperture and the straight X-ray area from the image, for example, according to the procedure shown in FIG. 4 (step S401; see FIG. 6 (c)). Further, the image processing device 12 creates a high frequency image 35 in which high frequency components of the subject region image 33 are extracted (step S402). FIG. 8A shows a metal region included in the subject region image 33 and a high-frequency image 35 around it. The image processing device 12 removes a weak signal component (noise component) from the high-frequency image 35 created by the processing in step S402 (step S403), and performs expansion processing for amplifying the object (step S404). In the expansion process, the thin line portion of the high-frequency image 35 created in step S402 is expanded according to a predetermined condition. The image processing device 12 acquires the standard deviation of each region obtained by the expansion processing and performs threshold processing (step S405). If the standard deviation is small, the region is the metal region 36A, and if the standard deviation is large, it is determined that the region is not a metal region (step S406). Through the above processing, the metal region 36A existing in the subject region is obtained.

  The pixel value of the pixel corresponding to the metal region 36A is not used for the calculation of the histogram in a histogram calculation process (step S204 in FIG. 3) described later.

  Returning to the description of FIG.

  The image processing device 12 calculates a histogram relating to pixel values for the image from which the subject region has been extracted and the metal region has been removed by the processing in steps S201 to S203 (step S204). The image processing device 12 calculates the separation point of the subject composition based on the histogram calculated in step S204 (step S205). The separation point is a boundary value for distinguishing different parts existing in the image, such as distinguishing the lung field region from the mediastinum region or distinguishing the bone region from the skin region. The calculated separation point is referred to as a control point when setting the γ curve.

  Here, a method for calculating the separation point will be described with reference to FIG.

  As described above, the image processing device 12 (separation point calculation unit 24) calculates a histogram relating to pixel values for an image from which the subject region has been extracted and the metal region has been removed (step S501). Further, the most frequent point of the created histogram is obtained (step S502).

  FIG. 10 (a) is an object region image 37 with the metal removed from the chest. Hereinafter, this is referred to as a chest image 37. It is assumed that the histogram 61 shown in FIG. 10B is obtained from the chest image 37 in FIG. The horizontal axis of the histogram 61 is the pixel value, and the vertical axis is the frequency. The image processing apparatus 12 smoothes the histogram 61, obtains the most frequent point 61c, which is the point with the highest frequency, and obtains a pixel value (most frequent value) corresponding to the most frequent point 61c (step S502). Further, the image processing apparatus 12 determines the separation point 61d based on the mode 61c obtained in step S502 and the slope of each pixel value in the histogram 61 (step S503).

  More specifically, the image processing apparatus 12 (separation point calculation unit 24) calculates the “slope start point” that is the absolute value of the slope between the mode 61c of the histogram 61 and the start point 61a of the histogram 61, and the mode. “Inclination end point” which is an absolute value of the inclination between 61c and the end point 61b of the histogram 61 is obtained. Then, the slope start point and the slope end point are compared, and if the slope end point is larger, the point that takes the smallest value among the absolute values of the slope of the histogram 61 at each point between the start point 61a and the mode 61c Is the separation point.

  When the inclination start point is larger, the separation point 61d is the point having the smallest value among the absolute values of the inclination of the histogram 61 at each point between the mode 61c and the end point 61b.

  The chest image 37 in FIG. 10 will be described as an example. In the mediastinum region and lung field region, the mediastinum region shows a larger average pixel value. Therefore, when the “slope end point” of the histogram 61 is larger, the mode 61c is in the mediastinum region, and when the “slope start point” is larger, the mode 61c is in the lung field region. When the most frequent point is in the mediastinum region (when the slope end point is larger), the absolute value of the slope in the histogram from the start point to the most frequent point is calculated, and the point with the smaller slope is calculated. When the most frequent point is in the lung field region (when the inclination start point is larger), the absolute value of the inclination in the histogram from the most frequent point to the end point is calculated, and the point with the smaller inclination is calculated. A point having a small slope of the histogram is a separation point 61d between the lung field region and the mediastinum region.

  Similarly, for the bone image 38 in FIG. 11, a histogram 62 shown in FIG. 11B is obtained from the metal-removed subject region image 38 in FIG. 11A.

  The image processing device 12 (separation point calculation unit 24) is configured to obtain an “inclination start point” that is an absolute value of an inclination between the mode 62c of the histogram 62 and the start point 62a of the histogram 62, and an end point of the mode 62c and the histogram 62. Each “tilt end point”, which is the absolute value of the slope with respect to 62b, is obtained. If the “tilt end point” of the histogram 62 is larger, the mode 62c is in the bone region, and if the “tilt start point” is larger, the mode 62c is in the skin region. When the most frequent point 62c is in the bone region (when the inclination end point is larger), the absolute value of the inclination in the histogram from the start point 62a to the most frequent point 62c is calculated, and the point with the smaller inclination is set as the separation point 62d. When the most frequent point 62c is in the skin region (when the inclination start point is larger), the absolute value of the inclination in the histogram from the most frequent point 62c to the end point 62b is calculated, and a point with a smaller inclination is calculated. A point with a small inclination is a separation point 62d between the bone region and the skin region.

  Returning to the description of FIG.

  When the histogram separation points are calculated by the methods shown in FIGS. 9 to 11, the image processing apparatus 12 creates a γ curve using the calculated separation points as control points (step S206 in FIG. 3).

  FIG. 12 shows an example of creating a γ curve in the chest image 37. 12A is a histogram 61 for the subject region of the chest image 37, and FIG. 12B is an example of the γ curve 71. FIG. The horizontal axis of the histogram 61 in FIG. 12 (a) and the horizontal axis of the γ curve 71 in FIG. 12 (b) coincide with each other to indicate pixel values.

  As shown in FIG. 12, in addition to the start point 61a and end point 61b of the histogram 61, the shape of the γ curve 71 is adjusted with the separation point 61d as the control points 7b, 7d and 7c, respectively. For example, in order to increase the contrast of the lung field region, the control point corresponding to the separation point 61d is increased so that the slope between the control point 7b corresponding to the start point 61a and the control point 7c corresponding to the separation point 61d is increased. Set the 7c position (output value). In this way, by making the output value of the separation point adjustable, a desired contrast can be given to a desired region of the subject region. In addition to the start point 61a, the end point 61b, and the separation point 61d of the histogram 61, the point 7a (bit minimum value “0”) corresponding to the minimum value of the entire histogram and the point 7e (bit maximum value. For example, corresponding to the maximum value) , “255”, etc.) as control points, the density range and contrast of the entire image can be freely adjusted.

  FIG. 13 shows an example of creating a γ curve in the bone image 38. FIG. 13A is a histogram 62 for the subject region, and FIG. 13B is an example of the γ curve 72. The horizontal axis of the histogram 62 in FIG. 13 (a) coincides with the horizontal axis of the γ curve 72 in FIG. 13 (b) to indicate pixel values.

  As shown in FIG. 13, in addition to the start point 62a and the end point 62b of the histogram 62, the shape of the γ curve 72 is adjusted with the separation point 62d as the control points 7b, 7d, and 7c, respectively. For example, in order to increase the contrast of the bone region, the output value of the separation point 7c is set so that the slope between the separation point 7c and the end point 7d is increased. In this way, by making the output value of the separation point adjustable, a desired contrast can be given to a desired region of the subject region. In addition to the start point 61a, the end point 62b, and the separation point 62d of the histogram 62, a point 7a corresponding to the minimum value of the entire histogram and a point 7e corresponding to the maximum value are added to the control points, so that the density range and contrast of the entire image can be obtained. Can be adjusted freely.

  In the examples of FIGS. 12 and 13, it is desirable that the γ curves 71 and 72 have a smooth curve shape by approximately interpolating the control points 7a to 7e.

  Further, the output width (width in the vertical axis direction) between the start point 7b and the end point 7d of the histogram can be expanded from the bit maximum width (from the bit minimum value point 7a to the output width of the bit maximum value point 7e).

  Returning to the description of FIG.

  When the γ curve is created, the image processing device 12 executes gradation conversion processing using the γ curve for the image 30 to be processed (step S207 in FIG. 3), and the gradation value is adjusted. Create diagnostic images. The image processing device 12 stores the created diagnostic image in the storage device 13 separately from the raw data (original image data 30) and sends it to the control device 11. The control device 11 displays the diagnostic image with the adjusted gradation on the display device.

  FIG. 14 shows an example of an operation screen 8 (user interface) suitable for the present embodiment.

  In the operation screen 8 shown in FIG. 14, a γ curve display area 81 and operation button groups 82 to 85 are provided. The operation buttons 82 and 83 are buttons for adjusting the region of interest contrast, and the output value of the separation point 7c is changed to “+” (large) and “−” (small), respectively. The operation buttons 84 and 85 are buttons for adjusting the overall contrast of the image, and the widths of the output values of the start point 7b and the end point 7d are changed to “+” (wide) and “−” (narrow), respectively. Further, the image for which the gradation value is being adjusted may be displayed in the operation screen 8. In this case, it is desirable that an image whose gradation is adjusted in real time is displayed in the image display area 86 as the shape of the γ curve is changed.

  The user interface is not limited to the example of the operation screen 8 in FIG. For example, the output values of the control points 7a to 7e may be adjusted by dragging each control point of the γ curve with a mouse or the like. Further, a histogram of the original image may be displayed together with the γ curve. For example, as shown in FIG. 12 and FIG. 13, if the input pixel value of the γ curve and the pixel value (horizontal axis) of the histogram are displayed in agreement, each feature point (start point, end point, separation point, etc.) of the histogram and γ The relationship with the control points of the curve can be displayed in an easy-to-understand manner for the operator.

  As described above, according to the diagnostic imaging apparatus 1 of the present embodiment, a histogram is calculated for a subject region of an image, a separation point of the subject composition is calculated based on the characteristics of the shape of the histogram, and the calculated separation point Are included in the control points of the γ curve. Therefore, it is possible to give a desired contrast to a desired area of the subject area. Further, since the image processing device 12 obtains the separation point of the subject composition (the boundary between the low density region and the high density region) based on the histogram, it is not necessary for the operator to set the boundary (separation point). A γ curve can be set for. Since the control points are the separation points of the histogram, and the control points are 3 points including the start and end points of the histogram, or 5 points including the bit maximum and minimum values, not only the density value and contrast of the region of interest, It is possible to prevent the occurrence of white crushing (low density side) and black crushing (high density side) in a subject area other than the region of interest. This makes it possible to appropriately adjust the contrast of the region of interest without reducing the amount of image information.

  The preferred embodiments of the present invention have been described in the above embodiments, but the present invention is not limited to the above-described embodiments. For example, in the above-described embodiment, an example of an image obtained by general imaging has been described, but the present invention can also be applied to a case of fluoroscopy. In the case of fluoroscopy, if the same gradation processing as that of the above-described embodiment is applied to the image of each frame, an image in which a desired region is expressed with a desired grayscale can be displayed even in fluoroscopy. In addition, it is obvious that those skilled in the art can come up with various changes and modifications within the scope of the technical idea disclosed in the present application, and these naturally belong to the technical scope of the present invention. It is understood.

  1 diagnostic imaging device, 2 X-ray source, 3 subject, 4 couch top, 5 X-ray detector, 10 console, 11 control device, 12 image processing device, 13 storage device, 14 display device, 15 input device, 20 Image generation unit, 21 Image data acquisition unit, 22 Subject area extraction unit, 23 Histogram calculation unit, 24 Separation point calculation unit, 25 Tone setting unit, 26 Display control unit, 61, 62 Histogram, 61a Histogram start point, 61b Histogram end point , 61c Mode, 61d Separation point, 71, 72 γ curve, 7a Control point (bit minimum value), 7b Control point (histogram start point), 7c Control point (separation point), 7d Control point (histogram end point), 7e Control point (bit maximum value), 8 operation screens (user interface)

In order to achieve the above-described object, the present invention provides an X-ray source that irradiates a subject with X-rays, an X-ray detector that is disposed opposite to the X-ray source and detects transmitted X-rays of the subject, and the X-rays An image processing device that generates image data based on transmitted X-rays detected by a detector, a storage device that stores image data generated by the image processing device, and a storage device that stores image data to be processed A subject region extraction unit that extracts a subject region from the acquired image data, a histogram calculation unit that calculates a histogram relating to pixel values of the subject region image obtained by the subject region extraction unit, and the histogram calculation unit A separation point calculation unit that calculates a separation point of the subject composition based on the calculated histogram, and gradation information for displaying the image data using the separation point as a control point are set. A gradation setting section, and a display control section that performs gradation conversion on the image data to be processed based on the gradation information set by the gradation setting section and displays the image data on a display device. The diagnostic imaging apparatus.

Also, to get the transmission X-ray of the Utsushitai to generate image data based on the obtained transmission X-ray, and storing in the storage device, and acquires image data to be processed object from the storage device, calculating and extracting a subject region from the acquired image data, a step of calculating a histogram of pixel values of the previous SL subject region image object area is extracted, the separation point of the subject composition based on the previous SL histogram When the steps of setting a gradation information in displaying the image data the previous SL separation point as a control point, before the image data that is the processing target and the gradation conversion based on Kikaicho information, the display device And a step of displaying the gray level information.

1 is an overall configuration diagram of a diagnostic imaging apparatus 1 according to the present invention. Flow chart showing the overall flow of X-ray image display processing Flow chart showing the procedure of display gradation processing Flow chart showing the procedure of subject area extraction processing The figure which shows the example of the image used in each step of an X-ray aperture removal process. (a) an example of the high-frequency component image 30, (b) an example of an image ( line image after Hough transform 31) in which a straight line is detected by the Hough transform , One case The figure which shows the example of the image used in each step of a direct X-ray area | region extraction process. (a) Example of X-ray aperture removal image 32, (b) Example of histogram 6 of X-ray aperture removal image 32, (c) Example of subject region image 33 Flow chart showing the procedure of metal removal process (a) Example of high-frequency image 35, (b) Image obtained by extracting metal region by expansion processing after removing noise from high-frequency image 35 (metal region extraction image 36) Flow chart showing the procedure of separation point calculation processing (a) Chest subject region image (chest image) 37 example, (b) Histogram 61 of chest image 37 in (a) (a) Example of bone region subject region image (bone image) 38, (b) Histogram 62 of bone image 38 in (a) Setting example of γ curve 71 based on histogram 61 Example of setting γ curve 72 based on histogram 62 Example of operation screen 8 which is a user interface

Diagnostic imaging apparatus according to the present invention, the X-ray source for irradiating X-rays to an object, the X-ray detector arranged opposite the X-ray source detect the transmitted X-rays of the subject, the X-ray detector An image processing device that generates image data based on transmitted X-rays detected in this way, a storage device that stores image data generated by the image processing device, and image data to be processed are acquired from the storage device. Calculated by the subject region extraction unit that extracts the subject region from the acquired image data, the histogram calculation unit that calculates the histogram related to the pixel value of the subject region image obtained by the subject region extraction unit, and the histogram calculation unit. A separation point calculation unit that calculates a separation point of a subject composition based on a histogram, and a gradation setting that sets gradation information when displaying the image data using the separation point as a control point And a display control unit for converting the gradation of the image data to be processed based on the gradation information set by the gradation setting unit and displaying the converted image data on a display device.

Further, the separation point calculation unit obtains a mode point of the histogram, and a slope start point which is an absolute value of a slope between the mode point and the start point of the histogram, and a slope between the mode point and the end point of the histogram. of the absolute value slope ending respectively, it said comparing the slope starting point and the tilt end point, when towards the tilt end point is large in the histogram at each point of between the slope start point to the modal point The point that takes the smallest value among the absolute values of the slope is the separation point, and when the slope start point is larger, the absolute value of the histogram slope at each point between the mode point and the slope end point The point having the smallest value is defined as a separation point.

Further, the image processing apparatus further includes a metal removal processing unit that removes the metal region from the subject region, and the histogram calculation unit calculates the histogram related to the pixel value of the subject region image from which the metal region has been removed by the metal removal processing unit.

Gradation information setting method according to the present invention, the image acquires the transmission X-ray of the Utsushitai to generate image data based on the obtained transmission X-ray, to a step of storing in the storage device, the processing target retrieve data from the storage device, and extracting a subject region from the acquired image data, a step of calculating a histogram of pixel values of the previous SL subject region image object area is extracted, based on the previous SL histogram image to the processing target based and setting calculating a separation point of the subject composition, the gradation information for displaying the image data the previous SL separation point as a control point, before Kikaicho information Converting the gradation of the data and displaying the data on a display device.

FIG. 4 shows an example of the procedure for subject area extraction processing. As shown in FIG. 4, the image processing apparatus 12 first extracts an X-ray aperture region from the image. The image processing device 12 creates a high-frequency component image 30 of the image (step S301; see FIG. 5 (a)), and performs a Hough transform (linear voting) on the direction of the diaphragm side based on the high-frequency component image 30. Then, a straight line candidate is detected (step S302; FIG. 5 (b) Hough transformed image 31 ). Further, the image processing apparatus 12 determines whether the line candidate is an object in the subject 3 or an area indicating the X-ray aperture 2b on the condition that the line candidate is located outside the line candidate obtained in step S302 (step S302). S303). The black frame region of the X-ray aperture removal image 32 shown in FIG. 5 (c) is a region removed from the high-frequency component image 30 as an X-ray aperture region.

Next, the image processing apparatus 12 directly extracts an X-ray region. First, the image processing apparatus 12 creates an X-ray aperture removed image 32 from which the X-ray aperture region has been removed from the high-frequency component image 30 to be processed by the processing in steps S301 to S303 (step S304; FIG. 6 (a)). . The image processing device 12 calculates a histogram 6 relating to pixel values for the X-ray aperture removed image 32 (step S305; see FIG. 6B). Based on the histogram 6 calculated in step S305, the image processing device 12 performs threshold determination processing using a predetermined luminance value as a threshold (step S306), and removes the high luminance value region (step S307). By the processing from step S304 to step S307, an area such as air outside the subject area is removed as in the subject area image 33 shown in FIG. 6C, and only the subject area remains.

When the subject area is extracted from the high frequency component image 30 to be processed by the process of step S201, the image processing device 12 determines whether or not the extracted subject area includes metal (step S202). If metal is included (step S202; Yes), a metal removal process is executed (step S203).

The chest image 37 in FIG. 10 will be described as an example. In the mediastinum region 37b and lung field region 37a , the mediastinum region 37b shows an average larger pixel value. Therefore, when the “slope end point” of the histogram 61 is larger, the mode 61c is in the mediastinum region 37b , and when the “slope start point” is larger, the mode 61c is in the lung field region 37a . When the most frequent point is in the mediastinum region 37b (when the inclination end point is larger), the absolute value of the inclination in the histogram from the start point to the most frequent point is calculated, and the point with the smaller inclination is calculated. When the most frequent point is in the lung field region 37a (when the inclination start point is larger), the absolute value of the inclination in the histogram from the most frequent point to the end point is calculated, and the point with the smaller inclination is calculated. A point where the slope of the histogram is small is a separation point 61d between the lung field region 37a and the mediastinum region 37b .

Similarly, for the bone image 38 in FIG. 11, a histogram 62 shown in FIG. 11 (b) is obtained from the bone image 38 in FIG. 11 (a).

The image processing device 12 (separation point calculation unit 24) is configured to obtain an “inclination start point” that is an absolute value of an inclination between the mode 62c of the histogram 62 and the start point 62a of the histogram 62, and an end point of the mode 62c and the histogram 62. Each “tilt end point”, which is the absolute value of the slope with respect to 62b, is obtained. If the “tilt end point” of the histogram 62 is larger, the mode 62c is in the bone region 38b , and if the “tilt start point” is larger, the mode 62c is in the skin region 38a . When the most frequent point 62c is in the bone region 38b (when the inclination end point is larger), the absolute value of the inclination in the histogram from the start point 62a to the most frequent point 62c is calculated, and the point with the smaller inclination is set as the separation point 62d. When the mode 62c is in the skin region 38a (when the tilt start point is larger), the absolute value of the tilt in the histogram from the mode 62c to the end point 62b is calculated, and a point with a small tilt is calculated. A point with a small inclination is a separation point 62d between the bone region 38b and the skin region 38a .

As shown in FIG. 12, in addition to the start point 61a and end point 61b of the histogram 61, the shape of the γ curve 71 is adjusted with the separation point 61d as the control points 7b, 7d and 7c, respectively. For example, in order to increase the contrast of the lung field region 37a , the control corresponding to the separation point 61d is performed so that the inclination between the control point 7b corresponding to the start point 61a and the control point 7c corresponding to the separation point 61d is increased. Set the position (output value) of point 7c. In this way, by making the output value of the separation point adjustable, a desired contrast can be given to a desired region of the subject region. In addition to the start point 61a, the end point 61b, and the separation point 61d of the histogram 61, the point 7a (bit minimum value “0”) corresponding to the minimum value of the entire histogram and the point 7e (bit maximum value. For example, corresponding to the maximum value) , “255”, etc.) as control points, the density range and contrast of the entire image can be freely adjusted.

As shown in FIG. 13, in addition to the start point 62a and the end point 62b of the histogram 62, the shape of the γ curve 72 is adjusted with the separation point 62d as the control points 7b, 7d, and 7c, respectively. For example, in order to increase the contrast of the bone region 38b , the output value of the separation point 7c is set so that the inclination between the separation point 7c and the end point 7d is increased. In this way, by making the output value of the separation point adjustable, a desired contrast can be given to a desired region of the subject region. In addition to the start point 61a, the end point 62b, and the separation point 62d of the histogram 62, a point 7a corresponding to the minimum value of the entire histogram and a point 7e corresponding to the maximum value are added to the control points, so that the density range and contrast of the entire image can be obtained. Can be adjusted freely.

When the γ curve is created, the image processing apparatus 12 executes gradation conversion processing using the γ curve for the high-frequency component image 30 to be processed (step S207 in FIG. 3), and the gradation value is adjusted. Create a diagnostic image. The image processing device 12 stores the created diagnostic image in the storage device 13 separately from the raw data (original high frequency component image 30) and sends it to the control device 11. The control device 11 displays the diagnostic image with the adjusted gradation on the display device.

Claims (10)

An X-ray source that irradiates the subject with X-rays;
An X-ray detector disposed opposite to the X-ray source to detect transmitted X-rays of the subject;
An image processing device that generates image data based on transmitted X-rays output from the X-ray detector;
A storage device for storing image data generated by the image processing device;
A subject area extraction unit that acquires image data to be processed from the storage device and extracts a subject area from the acquired image data;
A histogram calculation unit that calculates a histogram related to pixel values of the subject region image obtained by the subject region extraction unit;
A separation point calculation unit that calculates a separation point of the subject composition based on the histogram calculated by the histogram calculation unit;
A gradation setting unit for setting gradation information when displaying the image data using the separation point as a control point;
A display control unit that performs gradation conversion on the image data to be processed based on the gradation information set by the gradation setting unit and displays the image data on a display device;
An image diagnostic apparatus comprising:   2. The diagnostic imaging apparatus according to claim 1, wherein the separation point calculation unit calculates the separation point based on a slope and a mode of the histogram.   The separation point calculation unit obtains the most frequent point of the histogram, and the absolute value of the inclination between the most frequent point and the histogram end point, and the absolute value of the inclination between the most frequent point and the histogram end point. The slope end point which is a value is obtained, the slope start point and the slope end point are compared, and if the slope end point is larger, the absolute slope of the histogram at each point between the slope start point and the most frequent point The point having the smallest value among the values is the separation point, and when the slope start point is larger, the smallest value among the absolute values of the slope of the histogram at each point between the mode point and the slope end point 3. The diagnostic imaging apparatus according to claim 2, wherein a point where the value is taken is a separation point.   2. The diagnostic imaging apparatus according to claim 1, wherein the gradation setting unit sets the gradation information using the start point and end point of the histogram as control points in addition to the separation point.   5. The image diagnosis apparatus according to claim 4, wherein the gradation setting unit further sets the gradation information using a bit minimum value and a bit maximum value as control points.   2. The diagnostic imaging apparatus according to claim 1, wherein the gradation setting unit sets the gradation information so as to form a curve by approximate interpolation. A metal removal processing unit for removing the metal region from the subject region;
2. The diagnostic imaging apparatus according to claim 1, wherein the histogram calculation unit calculates the histogram for a subject region image from which a metal region has been removed by the metal removal processing unit.   8. The diagnostic imaging apparatus according to claim 7, wherein the metal removal processing unit includes a process of determining whether or not the metal is a metal based on a standard deviation of a density value of each region included in the image data. .   2. The diagnostic imaging apparatus according to claim 1, further comprising a user interface that displays a γ curve as the gradation information and an operation unit for changing a position of the control point in the γ curve. An image processing device acquires transmitted X-rays of a subject, generates image data based on the acquired transmitted X-rays, and stores them in a storage device;
An image processing device acquiring image data to be processed from the storage device, and extracting a subject area from the acquired image data;
An image processing device calculating a histogram relating to pixel values of a subject region image from which the subject region has been extracted; and
An image processing device calculating a separation point of the subject composition based on the histogram;
A step of setting gradation information when the image processing apparatus displays the image data using the separation point as a control point;
An image processing device gradation-converting the image data to be processed based on the gradation information and displaying the image data on a display device;
The gradation information setting method characterized by including.

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