JP2010017370A - Density adjusting device, density adjusting method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve the visibility of a medical image when reading the image by controlling the influence of the change of the tissue caused by the aging of a subject. <P>SOLUTION: A CPU 11 of the density adjusting device 10 computes a breast area Sa in breast image data D obtained by an image generating device G, and computes a breast muscle area M1 from the breast area Sa. The CPU 11 corrects the density of the breast image data D based on the average density of pixels included in the breast muscle area M1. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a density adjustment device, a density adjustment method, and a program.

  In digital mammography MLO photography (inside / outside oblique direction photography), the subject's breast is pressed and photographed. It is encouraged to position the radiographing area so that not only the breast but also the greater pectoral muscles enter the radiographing area.

  MLO imaging is performed based on various imaging conditions that are appropriately determined. The imaging conditions include, for example, imaging conditions instructed to the imaging apparatus, subject positioning, and breast compression strength. In these photographing conditions, a reference for accurate photographing is set in advance. When photographing is performed in a state that does not satisfy this criterion, the acquired breast image becomes entirely black, or on the contrary, white or blurred. That is, it becomes a failure image. With such a failure image, the doctor cannot make an appropriate diagnosis.

In order to solve the above problem, for example, in the technique described in Patent Document 1, a region of interest desired by the user is set in the captured radiographic image, and the density and gradation of the region of interest are set in advance. The image processing conditions are automatically changed so that the region of interest is output at a preset density and gradation.
JP-A-7-271972

On the other hand, the great pectoral muscle imaged together with the breast is mainly composed of muscle (muscle tissue). The breast is composed of a mammary gland and fat. The mammary gland changes to fat due to the aging of the subject.
In mammography, the mammary gland is photographed white and the fat is photographed black. That is, when the subject is young, the whole breast region is photographed white (dense breast), and when the subject is a middle age, the whole breast region is photographed black (active rest). It will be.

  In the case of the technique described in Patent Document 1, it is possible to correct to an appropriate density by performing image processing on a failed image shot in a state where the criteria of the shooting conditions are not satisfied. However, the predetermined region of interest may be affected by the tissue change due to the aging of the subject as described above, and there is a possibility that accurate density correction cannot be performed.

  For example, in the case of digital mammography, as a technique for performing density correction according to the tissue of the subject, an area under the nipple is set as a region of interest, and a breast image is calculated based on a correction value calculated based on the density of the region of interest. It is also under consideration to perform overall density correction. However, as described above, since the tissues that make up the breast change with age, even if image correction processing is performed based on correction values calculated from a partial area of the breast, accurate correction processing is performed. May not be possible. That is, there is a possibility that a problem may occur that the normal mammary gland concentration is erroneously detected as an abnormal mammary gland.

  The present invention has been made in view of the above-described problems, and the object of the present invention is to suppress the influence of tissue change caused by aging of the subject and to improve the visibility when interpreting medical images. is there.

In order to solve the above-mentioned problem, the invention described in claim 1
Breast area extraction means for extracting a breast area in a breast image;
A region determination unit that extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit and determines a region of the extracted pectoral muscle region that refers to a concentration;
Density correction means for correcting the density of the breast image based on the density of the area determined by the area determination means;
Is provided.

The invention according to claim 2 is the invention according to claim 1,
Storage means for storing a reference concentration of the pectoral muscle region;
The density correction unit calculates a difference between an average density of the region determined by the region determination unit and a reference density stored in the storage unit, and shifts the density of the breast image based on the calculated difference. To correct the density.

The invention according to claim 3 is the invention according to any one of claims 1 and 2,
The region determination unit extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit, and among the extracted pectoral muscle region, a region and / or a lesion that has been imaged by overlapping the breast and pectoral muscles The area for which the density is referred to is determined by excluding the part area.

The invention according to claim 4
A breast region extraction step of extracting a breast region in a breast image;
A region determination step of extracting a pectoral muscle region in the breast region extracted by the breast region extraction step, and determining a region of the extracted pectoral muscle region that refers to a concentration;
A density correction step of correcting the density of the breast image based on the density of the region determined by the region determination step;
Have.

The invention according to claim 5 is the invention according to claim 4,
The density correction step calculates a difference between the average density of the region determined by the region determination step and the reference density stored in the storage unit, and shifts the density of the breast image based on the calculated difference. Correct the density.

The invention according to claim 6 is the invention according to any one of claims 4 and 5,
The region determination step extracts a pectoral muscle region in the breast region extracted by the breast region extraction step, and a region and / or a lesion in which the breast and pectoral muscles are imaged in the extracted pectoral muscle region. The area for which the density is referred to is determined by excluding the part area.

The invention described in claim 7
Computer
A breast region extraction means for extracting a breast region in a breast image;
A region determination unit that extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit, and determines a region whose density is referred to from the extracted pectoral muscle region;
Density correction means for correcting the density of the breast image based on the density of the area determined by the area determination means;
To function as.

The invention according to claim 8 is the invention according to claim 7,
The computer,
Further function as a storage means for storing a reference concentration of the pectoral muscle region,
The density correction unit calculates a difference between an average density of the region determined by the region determination unit and a reference density stored in the storage unit, and shifts the density of the breast image based on the calculated difference. To correct the density.

The invention according to claim 9 is the invention according to any one of claims 7 and 8,
The region determination unit extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit, and among the extracted pectoral muscle region, a region and / or a lesion that has been imaged by overlapping the breast and pectoral muscles The area for which the density is referred to is determined by excluding the part area.

  ADVANTAGE OF THE INVENTION According to this invention, the influence of the tissue change resulting from aging of a to-be-photographed object can be suppressed, and the visibility at the time of the interpretation of a medical image can be improved.

  Embodiments according to the present invention will be described below. However, the present invention is not limited to the illustrated example.

(Configuration of density adjusting device 10)
First, the configuration in the present embodiment will be described.
FIG. 1 shows an example of a functional configuration of the density adjustment apparatus 10 according to the present embodiment.
As shown in FIG. 1, the density adjusting apparatus 10 includes a CPU (Central Processing Unit) 11, an I / F (InterFace) 12, an operation unit 13, a display unit 14, a communication unit 15, a RAM (Random Access Memory) 16, and a ROM. (Read Only Memory) 17, a printer 18, and the like, and each unit is connected by a bus 19.

  The CPU 11 reads out system programs and various processing programs stored in the ROM 17 and develops them in the RAM 16, executes various processes including a density adjustment process described later in cooperation with the developed programs, and performs density adjustment. The operation of each part of the apparatus 10 is centrally controlled.

  The I / F 12 is an interface for connecting to the image generation apparatus G, and inputs image data generated by the image generation apparatus G to the density adjustment apparatus 10.

The image generation apparatus G is an apparatus that captures a breast of a patient as a subject and digitally converts the captured image to generate breast image data D. As the image generation device G, for example, a CR (Computed Radiography) device, an FPD (Flat Panel Detector) device, or the like is applicable.
In the present embodiment, the image generation device G generates breast image data D for one patient and inputs it to the density adjustment device 10.

  The operation unit 13 includes a keyboard including cursor keys, numeric keys, and various function keys, and outputs an operation signal corresponding to the pressed key to the CPU 11. Note that a pointing device such as a mouse or a touch panel may be included as necessary.

  The display unit 14 includes a monitor such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube), and displays a breast image or the like in accordance with an instruction of a display signal input from the CPU 11.

  The communication unit 15 includes a communication interface such as a network interface card, a modem, and a terminal adapter, and transmits / receives various information to / from external devices on the communication network. For example, the image data may be received from the image generation device G via the communication unit 15 or may be connected to an image server in a hospital via the communication unit 15.

  The RAM 16 forms a work area for temporarily storing various programs executed by the CPU 11, data processed by these programs, and the like.

The ROM 17 functions as a storage unit, and stores various programs executed by the CPU 11 and data such as parameters necessary for execution of processing by the programs or processing results. These various programs are stored in the form of readable program codes, and the CPU 11 sequentially executes operations according to the program codes.
Other computer-readable media other than the ROM 17 include a non-volatile memory such as a flash memory such as an SD (Secure Digital) card or a USB (Universal Serial Bus) memory, and a portable recording medium such as a CD-ROM. It is possible to apply. It is also possible to provide various data such as program data according to the present invention via a communication line by superimposing them on a carrier wave.

  The printer 18 forms and outputs an image on a recording medium such as a film based on the image data under the control of the CPU 11.

(Operation of the density adjusting device 10)
Next, the operation in this embodiment will be described.
In the density adjustment apparatus 10, when breast image data D is input from the image generation apparatus G, density adjustment processing described below is executed.
Note that in the normal case, the image generation apparatus G captures the left and right breasts of the subject. That is, left and right breast image data D are input from the image generation device G, respectively. In the density adjustment process described below, the density adjustment process similar to that for one breast is performed for the other breast. Therefore, for convenience of explanation, only the density adjustment process for one breast image data D will be described.

FIG. 2 shows a flowchart of density adjustment processing executed in the density adjustment apparatus 10. This process is realized by a software process in cooperation with the CPU 11 and a program stored in the ROM 17. Note that the pixel value of the breast image data D in the present embodiment indicates a density value.
The processing described below is executed by the CPU 11.

First, a breast region included in the input breast image data D is extracted (step S1).
FIG. 3 schematically shows the breast image data D. In step S1, from the breast image data D, an area where X-rays have passed through the subject (hereinafter referred to as breast area Sa) and an area where X-rays did not pass through the subject (hereinafter referred to as outside breast area Sb). Processing to sort is performed. By the process in step S1, the CPU 11 functions as a breast region extracting unit.

A known method may be used for the extraction process of the breast region Sa performed in step S1. For example, it is extracted as in the following (1-1) to (1-3).
If the breast image data D is 12-bit grayscale data, each pixel is expressed by a pixel value of 0 to 4095. Of the breast image data D, the breast region is photographed white. For example, the pixel values of the breast region Sa are concentrated between low regions (for example, 0 to 1000). Conversely, the area other than the subject, that is, the region where the X-rays do not pass through the subject are photographed in black. For example, in the case of 12-bit data, the pixel values of the extramammary region Sb are concentrated between high regions (for example, 4000 to 4095). In the following (1-1) to (1-3), the breast image data D is discriminated from the breast region Sa and the extramammary region Sb based on the tendency of the low region and the high region to be binarized. become.

(1-1) Binarization Processing of Pixels of Breast Image Data D First, the breast image data D is segmented into certain sections (for example, 8 pixels square) (hereinafter, each of the certain sections is simply referred to as a segment). .
Then, the average pixel value of each segment is compared with a threshold value. This threshold value is a threshold value for considering the breast region Sa, and is stored in the ROM 17 in advance. Each segment is binarized by being compared with a threshold value. That is, processing is performed so that a segment indicating a pixel value smaller than the threshold is “1” and a segment indicating a pixel value larger than the threshold is “0”.
Then, the binarized value of each segment is corrected based on the morphology. Specifically, if all the segments around the segment whose binarized value is “0” are all “1”, this segment is likely to be the breast region Sa, so the binary value of this segment The corrected value is corrected, for example, by correcting it to “1”.
Through the above processing, the breast image data D can be binarized for each segment. Note that binarization may be performed for all pixels without dividing the breast image data D into segments, but in this embodiment, binarization is performed for each segment as described above in order to reduce the processing load. I will do it.

(1-2) Dividing the breast image data D into two Next, the breast image data D is equally divided into two in the vertical direction. That is, the breast image data D is divided into left and right parts. Among the two divided areas, a bright area (that is, an area with many white pixels) is determined. As a determination method, for example, an area having a larger number of segments having a binarized value “1” of the two left and right areas is determined as a bright area. That is, it is determined that the breast is present in the region with the larger number of white pixels.

(1-3) Breast Area Candidate Extraction Next, breast area Sa candidates are extracted from the bright area of the breast image data D. Specifically, first, the size of the area where the binarized value of each segment is “1” is determined. If it is determined that this region is sufficiently wider than a predetermined threshold, the region is set as a candidate for the breast region Da. When it is determined that it is not wider than a predetermined threshold value, the following adjustment process is performed.
Four segments (up / down / left / right segments) surrounding a certain segment (referred to as a target segment) are defined as segments of interest. When the average pixel value of the target segment is smaller than a threshold value predetermined in the ROM 17 (a value different from the threshold value used in (1-1) may be used), the segment of interest has a bipolar value. Of these, “1” is set. On the contrary, if the average pixel value of the target segment is larger than a predetermined threshold value, “0” of the bipolar values is set in the segment of interest. The adjustment process is performed in this manner, and it is determined again whether the area of the binarized value “1” is sufficiently wide. If a candidate region for the breast region Sa is still not found, the other region (the other of the regions obtained by dividing the breast image data D into two regions, that is, the region that is not bright) is searched. If no candidate is still found, the whole breast image data D is searched.
The candidate extracted in this way is defined as a breast region Sa.

Returning to FIG. 2, the pectoral muscle region M1 is extracted from the breast region Sa calculated in step S1 (step S2).
A known method may be used for the extraction processing of the pectoral muscle region M1 performed in step S2. For example, the extraction process of the pectoral muscle region M1 performed in step S2 is calculated as (2-1) to (2-5) below.

(2-1) Edge Enhancement Processing First, filter processing is performed by a Prewitt filter with each pixel of breast image data D as a target pixel. As a result, breast image data with enhanced edges (hereinafter referred to as breast image data D1 for distinction) is acquired. The pixel value of each pixel of the breast image data D1 is a value indicating edge strength.

Hereinafter, as shown in FIG. 4A, the positions of the respective pixels in the breast image data D1 are coordinates (X, Y) in which the left-right direction of the breast in the breast image data D1 is the X axis and the vertical direction is the Y axis. ). Further, the pixel value of the coordinates (X, Y) in the breast image data D1 is represented as V (X, Y). Further, the coordinates of the image end in the X-axis direction are represented as X _max , and the image end in the Y-axis direction is represented as Y _max .

(2-2) Extraction of Skin Line SL Next, a skin line SL that is a boundary point between the breast region Sa and the extramammary region Sb in the breast image data D1 is extracted. The boundary between the breast area Sa and the extramammary area Sb calculated in step S1 may be used as the skin line SL. However, since the edge enhancement processing is performed in (2-1), the skin line SL is as follows. To extract.
For each Y coordinate (0 to Y _max ) of the breast image data D1, a search is performed in the X-axis direction, and a coordinate S (Y) that maximizes V (X, Y) is extracted. Thereby, the edge in each Y coordinate of the breast image data D1 is extracted. As shown in FIG. 4A, the extracted edge is a boundary point between the breast region Sa and the non-mammal region Sb in the breast image data D1, and constitutes a skin line SL.

(2-3) Determination of the start point of the pectoral muscle line L search The coordinate A several pixels below the coordinate S (0) (the position of the skin line SL at the image end of the Y coordinate 0) at which V (X, 0) is maximum. Is the starting reference point. The following processing for searching for the search start point B of the pectoral muscle line L is performed while shifting the reference point pixel by pixel from the coordinate A in the X-axis direction.
First, as shown in FIG. 4A, the width in the Y-axis direction of the breast image data D1 in increments of 1 ° with respect to each reference point in the range of 0 to −30 ° with respect to the Y-axis direction. Search lines la0 to la30 having a length of 1/5 are set. Next, the average value of the pixel values on the search lines la0 to la30 is calculated. After calculating the average value of the pixel values on the search lines la0 to la30 for all the reference points, the reference point of the search line having the maximum calculated average value is determined as the pectoral muscle line search start point B. .
At this time, when the pectoral muscle line search start point B is close to the right end (X _max ) of the image, for example, from the right end to 10 pixels, it is determined that there is no pectoral muscle region M1. When the calculated maximum average value is smaller than a predetermined threshold value, for example, 300, it is determined that there is no pectoral muscle region M1. If it is determined that the pectoral muscle region M1 is absent, for example, an error message or the like is displayed on the display unit 14, and the density adjustment process ends.

(2-4) Search for Boundary (Pectoral Muscle Line L) Between Pectoral Muscle Region M1 and Breast Region Sa FIG. 4B shows an enlarged view near the pectoral muscle line search start point B. FIG. As shown in FIG. 4B, the width of the breast image data D in the Y-axis direction is 1 in increments of 1 ° with respect to the range of the angle ± 9 ° from the Y-axis direction with the pectoral muscle line search start point B as the base point. Search lines lb0 to lb18 having a length of / 5 are set. Next, the average value of the pixel values on the search lines lb0 to lb18 is calculated. Then, the search line lbn (n is an integer from 0 to 18) having the maximum calculated average value is determined as the pectoral muscle line L.
Next, similar processing is performed using a point that is 1/10 of the width in the Y-axis direction from the pectoral muscle line search start point B as a base point. Thereafter, the same processing is performed with a point that is 1/10 of the width in the Y-axis direction from the point set as the previous base point. By repeating the same process until the image end is reached, the pectoral muscle line L is extracted.
When the maximum average value of the search lines lb0 to lb18 is smaller than a predetermined threshold (for example, 300), it is determined that the pectoral muscle line L is unclear. When there are two or more base points where the maximum average value of the search lines lb0 to lb18 is greater than the threshold value, a quadratic approximate curve is drawn from these base points, and this curve is extracted as the pectoral muscle line L. When the base point where the maximum average value of the search lines lb0 to lb18 is greater than the threshold is 1 or less, the above processing is executed with the pectoral muscle line search start point B shifted by one pixel in the Y-axis direction.

(2-5) Extraction of the pectoral muscle region M1 When the pectoral muscle line L is extracted, the extracted pectoral muscle line L and the region surrounded by the image end opposite to the skin line SL in the breast image region Sa (A region indicated by rough points in FIGS. 4A and 4B) is extracted as the pectoral muscle region M1.

Returning to FIG. 2, among the pectoral muscle regions M <b> 1 extracted in step S <b> 2, regions that do not refer to density (hereinafter referred to as density reference exclusion regions) are determined and excluded (step S <b> 3). Specifically, the pectoral muscle region M1 is extracted from the breast region Sa in step S2, and a region in the pectoral muscle region M1 near the pectoral muscle line L (hereinafter referred to as a mammary gland overlap region T1) is a pectoral muscle region. Not taken into account as the concentration of M1. This is because the mammary gland overlap region T1 may be a region in which the mammary gland and the pectoral muscle are imaged due to poor positioning during imaging. That is, if the density of the mammary gland overlap region T1 is included in the density calculation of the pectoral muscle region M1, there is a possibility that the accurate concentration as a muscle tissue cannot be calculated.
In addition, even when a lesion such as lymphoproliferation is included in the pectoral muscle region M1, a region in the vicinity of this lesion (hereinafter referred to as lymphoproliferative region T2) is excluded from the density calculation. This is because the concentration of the lymph hypertrophy region T2 and the concentration of tissues such as normal lymph are different.

  In the present embodiment, the aforementioned mammary gland overlap region T1 and lymphoproliferative region T2 are determined as the concentration reference exclusion region. The concentration reference exclusion region may be a region that is not regarded as a normal muscle tissue, and is not limited to that in the present embodiment. For example, the ROM 17 may hold a lesion area other than lympho-hypertrophy and a density reference exclusion area preset by the user.

Hereinafter, the process in step S3 will be described.
The determination and exclusion processing of the mammary gland overlap region T1 and the lymphoproliferative region T2 performed in step S3 is calculated as follows (3-1) to (3-3).

(3-1) Determination of the mammary gland overlap region T1 First, the determination of the mammary gland overlap region T1 will be described.
Hereinafter, as shown in FIG. 5A, in the breast image data D, the coordinates of the pixels on the pectoral muscle line L are (X _max −X _muscle [k], k). Note that k is an arbitrary integer of 0 to Y _max .
That is, in the pectoral muscle line L, the coordinate where the value of Y is 0 (hereinafter referred to as coordinate P1) is (X _max −X _muscle [0], 0).
Also, the value of k when X _muscle [k] is 0 is assumed to be Y _muscleMAX . That is, in the pectoral muscle line L, the coordinates of the X value of X _max (hereinafter referred to as coordinates P2) are (X _max , Y _muscleMAX ).

  In the present embodiment, as a reference for the mammary gland overlap region T1, the coordinate P2 and the X coordinate are the same, and the value of the Y coordinate is 2/3 of the Y coordinate of P2 (hereinafter referred to as the coordinate P3). An area delimited by a straight line connecting P1 (shown by a broken line in FIG. 5 and hereinafter referred to as a straight line L1) is used. That is, in the pectoral muscle region M1, a region having the same X coordinate value and a larger Y coordinate value than the straight line L1 is defined as a mammary gland overlap region T1. The method for determining the mammary gland overlap region T1 is not limited to this as long as it is determined from the pectoral muscle region M1, the pectoral muscle line L, and the like.

(3-2) Excluding the mammary gland overlapping region T1 from the pectoral muscle region M1 Next, the mammary gland overlapping region T1 is excluded from the pectoral muscle region M1. Hereinafter, a region excluding the mammary gland overlap region T1 from the pectoral muscle region M1 (hereinafter referred to as pectoral muscle region M2, which is a region indicated by shading in FIG. 5A) will be specifically shown.

First, the straight line L1 is expressed as Y = aX + b. Note that a and b are expressed by the following equations.

The pectoral muscle region M2 excluding the mammary gland overlap region T1 from the pectoral muscle region M1 is extracted as a region surrounded by the following expression.

(3-3) Confirmation and Exclusion of Lymphomegaly Region T2 Next, confirmation of the lymphatic hypertrophy region T2 included in the pectoral muscle region M2 will be described.
A known method may be used for determining and excluding the lymph hypertrophy region T2. For example, a method of determining the lymph hypertrophy region T2 by performing a determination using a curvature as described below may be used.

  The curvature is composed of signal components in three directions (X, Y, and Z axes) of the coordinates (X, Y) of the pixel included in the pectoral muscle region M2 and the pixel value of the pixel, that is, the density (Z). It is calculated by approximating the normal section of the pixel of interest with a circle from the curved surface obtained from the density distribution and obtaining the radius of the circle. The curvature is an index indicating whether the curved surface is convex or concave. That is, the larger the curvature in the positive direction, the more concave the curved surface, and the larger the curvature value in the negative direction, the convex shape. Therefore, the larger the absolute value of the curvature, the greater the density gradient in the vicinity of the target pixel.

Abnormal shadows such as lymphatic hypertrophy are generally classified into concave shapes. The pectoral muscle region M2 is divided into predetermined small regions, and an average value of curvature, a maximum value of curvature, a minimum value of curvature, and the like are calculated as feature amounts for each small region. This feature amount is compared with a preset threshold value. A small region having a feature amount equal to or greater than the threshold value, that is, a large concave region is calculated as a candidate region for lymphoproliferation.
In the present embodiment, when the candidate region for lymph hypertrophy is approximated to a circle and the diameter is 10 mm or less, it is recognized as normal lymph. That is, when the diameter of this approximate circle is 10 mm or more, the candidate region is determined as the lymphoproliferative region T2. However, the method of determining normal / abnormal lymph is not limited to this.
The lymphoproliferative region T2 calculated as described above is excluded from the pectoral muscle region M2 (hereinafter, this region is referred to as a concentration reference region M3).
FIG. 5B shows a lymphoproliferative region T2 and a concentration reference region M3. As shown in FIG. 5B, a region obtained by excluding the lymph hypertrophy region T2 from the pectoral muscle region M2 is the concentration reference region M3.
The CPU 11 functions as a region determination unit by the processing in step S2 and step S3. The density reference area M3 may be determined based on the pectoral muscle area T1, and the process of excluding the density reference exclusion area from the density reference area M3 in step S3 is not essential.

In step S4, the average density D _MuscleAve of the density reference region M3 calculated in step S3 is calculated (step S4). Specifically, the pixels included in the density reference area M3 are counted, and the number N of pixels in the density reference area M3 is acquired. A pixel value (density) of an arbitrary pixel included in the density reference region M3 is defined as D (x, y). The average density D _MuscleAve is calculated by dividing the sum of the pixel values of the pixels included in the density reference area M3 by the number N of pixels included in the density reference area M3 as in the following equation.

Next, the density of the breast image data D is corrected based on the average density D _MuscleAve calculated in step S4 (step S5). By the process in step S5, the CPU 11 functions as a density correction unit. In the following description, the density of the breast region Sa of the breast image data D is described as being corrected. However, the entire breast image data D may be similarly corrected.

Hereinafter, the density correction process of the breast region Sa performed in step S5 will be described.
The density at the arbitrary coordinates of the breast region Sa (that is, the pixel value) is D (x, y), and the density after correction in step S5 is D '(x, y). Further, assuming that a threshold predetermined in the ROM 17 (that is, a reference concentration of the pectoral muscle region) is D _standard , D ′ (x, y) is calculated by the following equation. Note that t in the following is an arbitrary constant from 0 to 1.

FIG. 6 shows the relationship between the density D (x, y) at an arbitrary coordinate of the breast region Da and the corrected density D ′ (x, y) by the above formula. As shown in FIG. 6, when the value of c is 0, that is, when the average density D _MuscleAve and the threshold value D _standard are equal, the density of the breast region Sa is not corrected.
Further, when the value of c is positive, that is, when the average density D _MuscleAve is smaller than the threshold value D _standard , it indicates that the density reference region M3 is photographed relatively white. In this case, the breast area Sa of the subject generally tends to be white, but as described above, the breast area Sa may be photographed black due to aging, and the density D (x, y) is corrected so as to be smaller (that is, whiter).
On the contrary, when the value of c is negative, that is, when the average density D _MuscleAve is larger than the threshold value D _standard , it indicates that the density reference region M3 is photographed relatively black. In this case, the breast area Sa of the subject generally tends to be black, but the breast area Sa may be photographed white because the subject is young, and the density D (x, y) of the breast area Sa is high. It will be corrected to be larger (that is, blacker).

  As described above, according to the density adjustment apparatus 10 in the present embodiment, the density is corrected so that the breast image data D having a white pectoral area is white as a whole by the density adjustment processing. On the other hand, the density is corrected so that the breast image data D in which the pectoral muscle region is black is entirely black. Therefore, since the correction value necessary for correcting the density of the breast image data D is determined based on the density calculated based on the pectoral muscle region with little tissue change caused by the aging of the object, Therefore, it is possible to perform appropriate density correction with little influence of tissue change caused by the image quality, and the reliability in diagnosis of a breast image is improved.

  In the present embodiment, the density reference exclusion region is determined from the pectoral muscle region, and the concentration of the concentration reference exclusion region is not calculated as the average concentration of the pectoral muscle region. That is, since the average density of the pectoral muscle area excluding the area that does not show normal density, such as a mispositioning imaging error or a lesioned part, is calculated, the density correction reliability can be further improved.

In addition, the description in this Embodiment mentioned above is a suitable example which concerns on this invention, and is not limited to this.
For example, the density correction in step S5 is performed based on the conversion formula as shown in FIG. 6, but the density correction is not limited to this as long as the density correction is performed based on the average density obtained from the pectoral muscle region. For example, a correspondence table of the average density of the pectoral muscle region and the correction value may be held so that the value of the table can be changed according to the user's preference.

  In addition, the detailed configuration and detailed operation of each device constituting the density adjusting device 1 can be changed as appropriate without departing from the spirit of the present invention.

It is a figure which shows the density | concentration adjustment apparatus in this embodiment. It is a flowchart which shows the density | concentration adjustment process which the density | concentration adjustment apparatus shown in FIG. 1 performs. It is a schematic diagram which shows the relationship between a breast area | region and an area | region outside a breast. It is the schematic diagram which expressed the breast image data by the coordinate, (a) is explanatory drawing explaining a pectoral muscle line search, (b) is an enlarged view near search start point. It is a schematic diagram of the breast image data for demonstrating the process which calculates a density | concentration reference exclusion area | region from a pectoral muscle area | region, (a) is a figure explaining a mammary gland duplication area | region, (b) explains a lymph hypertrophy disease area | region. It is a figure to do. It is a figure which shows the relationship of the density | concentration before and behind correction | amendment when density correction is performed by the density adjustment process.

Explanation of symbols

10 Density adjustment device 11 CPU
12 I / F
13 Operation unit 14 Display unit 15 Communication unit 16 RAM
17 ROM
18 Printer G Image generation device

Claims (9)

Breast area extraction means for extracting a breast area in a breast image;
A region determination unit that extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit and determines a region of the extracted pectoral muscle region that refers to a concentration;
Density correction means for correcting the density of the breast image based on the density of the area determined by the area determination means;
A concentration adjusting device comprising: Storage means for storing a reference concentration of the pectoral muscle region;
The density correction unit calculates a difference between an average density of the region determined by the region determination unit and a reference density stored in the storage unit, and shifts the density of the breast image based on the calculated difference. The density adjusting apparatus according to claim 1, wherein the density is corrected.   The region determination unit extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit, and among the extracted pectoral muscle region, a region and / or a lesion that has been imaged by overlapping the breast and pectoral muscles The density adjusting apparatus according to claim 1, wherein an area for which density is referred to is determined by excluding a part area. A breast region extraction step of extracting a breast region in a breast image;
A region determination step of extracting a pectoral muscle region in the breast region extracted by the breast region extraction step, and determining a region of the extracted pectoral muscle region that refers to a concentration;
A density correction step of correcting the density of the breast image based on the density of the region determined by the region determination step;
Concentration adjustment method.   The density correction step calculates a difference between the average density of the region determined by the region determination step and the reference density stored in the storage unit, and shifts the density of the breast image based on the calculated difference. The density adjustment method according to claim 4, wherein the density is corrected.   The region determination step extracts a pectoral muscle region in the breast region extracted by the breast region extraction step, and a region and / or a lesion in which the breast and pectoral muscles are imaged in the extracted pectoral muscle region. The density adjustment method according to claim 4, wherein an area for which density is referred to is determined by excluding a part area. Computer
A breast region extraction means for extracting a breast region in a breast image;
A region determination unit that extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit, and determines a region whose density is referred to from the extracted pectoral muscle region;
Density correction means for correcting the density of the breast image based on the density of the area determined by the area determination means;
Program to function as. The computer,
Further function as a storage means for storing a reference concentration of the pectoral muscle region,
The density correction unit calculates a difference between an average density of the region determined by the region determination unit and a reference density stored in the storage unit, and shifts the density of the breast image based on the calculated difference. The program according to claim 7, wherein the density is corrected.   The region determination unit extracts a pectoral muscle region in the breast region extracted by the breast region extraction unit, and among the extracted pectoral muscle region, a region and / or a lesion that has been imaged by overlapping the breast and pectoral muscles The program according to any one of claims 7 and 8, wherein an area for which density is referred to is determined by excluding a part area.

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