JP5279995B2 - Area determination device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a domain definer which enables a highly precise extraction of a domain belonging to a prescribed constituent part from an image of an object. <P>SOLUTION: The device is provided with a contrast image acquisition part which acquires a contrast image showing the object with a contrast medium applied, a non-contrast image acquisition part which acquires a non-contrast image showing the object without the application of the contrast medium and a domain defining part which defines the domain belonging to a prescribed constituent part making up the object. The contrast image has a higher image density not only in a bone domain belonging to a bone of the object but also in some non-bone domains belonging to an organ, a blood vessel, a lesion and the like. However, the non-contrast image has a higher image density in the bone domain as compared with the non-bone domain. By utilizing such a characteristic, the domain belonging to a bone or the like can be defined on the contrast image easily and at a higher precision. <P>COPYRIGHT: (C)2008,JPO&amp;INPIT

Description

  The present invention relates to an area determination device for determining an area belonging to a predetermined component constituting an object from an image of the object.

  In the medical field, a medical image obtained by photographing the inside of a subject using radiation or the like is widely used for diagnosis of a medical condition of the subject. By using medical images for diagnosis, it is possible to grasp the progress of the medical condition of the subject without causing external damage to the subject, and to easily obtain information necessary for determining the treatment policy. it can.

  In recent years, a CR (Computed Radiography) device that obtains a digital medical image using radiation, a CT device (Computerized Tomography) that obtains a tomographic image of a subject using radiation, and a tomographic image of a subject using a strong magnetic field. An MRI apparatus (Magnetic Resonance Imaging) or the like for obtaining a digital image has been widely used, and a digital medical image is generally used instead of a medical image using a conventional X-ray film or the like. Digitalization of medical images makes it easy to perform image processing on medical images, and displays a plurality of medical images taken at different times for the same subject on a monitor, on a medical image, Enlarging and displaying an image portion presumed to be a lesion has been widely performed.

  Here, in an original medical image obtained from a CT apparatus or the like, a bone region belonging to a bone generally has a considerably higher image density than a non-bone region other than a bone region. There is a problem that even if there is a lesion inside, it is difficult to find because the lesion is lost in the bone. For this reason, a diagnosis is performed using a bone-removed image obtained by extracting a bone from a medical image and removing the extracted bone. As a bone extraction method for extracting bones in a medical image, a region having an image density equal to or higher than a reference density is obtained from a medical image by utilizing the fact that the image density of the bone area is higher than the image density of the non-bone area. The extraction method is widely known. However, in a contrast image taken with a contrast agent being applied to the subject, the blood vessel region belonging to the blood vessel has a high image density like the bone region, and the region having an image density higher than the reference concentration from the contrast image There is a problem that some non-bone regions are extracted together with the bone region.

In this regard, Patent Document 1 discloses that a high reference density in a medical image is obtained using a high reference density that is close to the maximum value of the image density in the bone region and a low reference density that is close to the maximum value of the image density in the blood vessel region. A technique is described in which a high density area having an image density higher than the density is removed, and an overlapping area having an image density higher than the low reference density and overlapping the high density area is also removed. According to the technique described in Patent Document 1, it is unclear whether the region is a bone or a blood vessel, and the overlapping region overlapping with the high concentration region is removed. In addition to the bone region, the problem that the blood vessel region is removed can be reduced.
JP 11-318883 A

  However, in a contrast image obtained by photographing the subject's chest or abdomen, some blood vessel regions may have a higher image density than the bone region. With the technique described in Patent Document 1, the image density is higher than the blood vessel region. There is a problem that a low bone region cannot be extracted. On the other hand, if the reference density is set low so that a bone area having a low image density can be reliably extracted, the detected area increases and the bone area is connected to the surrounding area. Can no longer be extracted.

  In view of the circumstances described above, an object of the present invention is to provide an area determination device that can accurately extract an area belonging to a predetermined component from an image of a subject.

The region determination device of the present invention that achieves the above object includes a contrast image acquisition unit that acquires a contrast image in which a subject is captured in a state in which a contrast agent is poured,
A non-contrast image acquisition unit for acquiring a non-contrast image in which the subject is captured in a state where no contrast medium is injected;
An area determining unit that determines an area belonging to a predetermined constituent part constituting the subject among areas on the contrast image based on at least the non-contrast image.

  When a medical image of a subject is photographed, first, the subject is photographed in a state in which no contrast agent is poured, and then the subject is photographed in a state in which a contrast agent is poured. In general, non-contrast images are acquired as a set. In contrast-enhanced images, in addition to bone regions belonging to the subject bone, some non-bone regions belonging to organs, blood vessels, lesions, etc. also have high image density. It has a much higher image density than the area. By using such characteristics of contrast-enhanced images and non-contrast-enhanced images, regions belonging to components such as bones on contrast-enhanced images can be easily and accurately determined.

  In the region determination device according to the present invention, it is preferable that the region determination unit determines a region belonging to the bone of the subject among the regions on the contrast image.

  For example, a bone region belonging to a bone is extracted from the contrast image, and further, the bone region is removed from the contrast image, so that a lesion in the contrast image can be easily seen.

Moreover, in the area determination device of the present invention,
“A non-contrast image is provided with a reference region extraction unit that extracts a reference region belonging to a constituent part using a predetermined extraction reference,
The region determination unit determines a region corresponding to the reference region extracted by the reference region extraction unit among regions on the contrast image as a region belonging to the constituent part.
This form is suitable.

  A contrast image and a non-contrast image are generally taken as a set at a time, and it is considered that constituent parts exist at substantially the same position in each image. By extracting the reference region belonging to the constituent part from the non-contrast image and extracting the region corresponding to the reference region from the contrast image, the region on the contrast image can be easily and accurately determined.

Moreover, in the area determination device of the present invention,
“A reference region extraction unit that extracts a reference region belonging to a constituent part from a non-contrast image using a predetermined extraction reference;
A candidate region extraction unit that extracts a candidate region from the contrast image using the same extraction criterion as the extraction criterion;
The region determination unit determines a region corresponding to the reference region extracted by the reference region extraction unit among the candidate regions extracted by the candidate region extraction unit as a region belonging to the constituent part.
This form is preferable.

  Once the candidate area is extracted from the contrast image, and further, the area corresponding to the reference area extracted from the non-contrast image is extracted from the candidate area, thereby improving the area extraction accuracy. Can do.

  In the region determination device of the present invention, it is preferable that the region determination unit determines a region corresponding to the reference region in consideration of a positional deviation between the contrast image and the non-contrast image. is there.

  By taking into account the positional deviation between the contrast-enhanced image and the non-contrast-enhanced image, a region on the contrast-enhanced image that corresponds to the reference region of the non-contrast-enhanced image can be determined with high accuracy.

Moreover, in the area determination device of the present invention,
“With a candidate region extraction unit that extracts a candidate region from a contrast image using a predetermined extraction criterion,
The region determination unit generates a difference image between a contrast image and a non-contrast image, and determines a region belonging to a constituent part among the regions extracted by the candidate region extraction unit based on the difference image. "
This form is also preferable.

  In the contrast image, the bone region and a part of the non-bone region have a high image density, and in the non-contrast image, the bone region has a high image density. By using a difference image between these contrast-enhanced image and non-contrast-enhanced image, a region belonging to a bone or the like can be easily determined.

  In the region determination device of the present invention, it is preferable that the region determination unit generates the difference image by correcting a positional deviation between the contrast image and the non-contrast image.

  By generating the difference image after correcting the positional deviation between the contrast image and the non-contrast image, the region on the contrast image can be accurately determined.

Moreover, in the area determination device of the present invention,
“A new candidate area extraction unit that extracts a new candidate area that satisfies an extraction criterion that is looser than an extraction criterion that is satisfied by a candidate area that has been confirmed as an area belonging to a constituent part,
The region determination unit is a region that belongs to the constituent part among the new candidate regions based on the adjacency relationship between the new candidate region extracted by the new region extraction unit and the region that has been determined to belong to the constituent part. Is to be established. ''
This form is preferable.

  By extracting a new region while gradually relaxing the extraction condition, it is possible to accurately extract a region belonging to a predetermined component in the contrast image.

  According to the present invention, it is possible to accurately extract a region belonging to a predetermined component from a subject image.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a schematic configuration diagram of a medical diagnosis system to which an embodiment of the present invention is applied.

  The medical diagnostic system shown in FIG. 1 includes an image generation device group 10 that captures a body of a subject to generate a medical image, a management server 20 that stores medical images, medical records, and the like, and a diagnostic device 30 that displays medical images. The image generation apparatus group 10 and the management server 20, and the management server 20 and the diagnosis apparatus 30 are connected via a network line.

  In this medical diagnosis system, an identification number for identifying each subject is assigned to the first medical examination subject, and the identification number is associated with a medical record showing the name, age, medical history, etc. of the subject. Registered in the management server 20.

  The image generation device group 10 includes a CR device 11 that irradiates a subject with radiation, reads the radiation transmitted through the subject and generates a digital medical image, and a CT device 12 that generates a tomographic image of the subject using radiation. In addition, an MRI apparatus (not shown) that generates a tomographic image of a subject using a strong magnetic field and radio waves, an ultrasonic apparatus (not shown) that generates a medical image by reading an ultrasonic echo, and the like are included. In the present embodiment, in the image generation device group 10, a subject is photographed without administering a contrast agent to generate a non-contrast image, and then the subject is photographed with a contrast agent administered, and a contrast image is obtained. Generated. A set of contrast image and non-contrast image generated by the image generation device group 10 is sent to the management server 20 together with an identification number for identifying a subject as a subject.

  When the contrast image, the non-contrast image, and the identification number are sent from the image generation device group 10, the management server 20 stores the set of the contrast image and the non-contrast image in association with the identification number. That is, in the management server 20, an identification number, a medical record of a subject to which the identification number is assigned, and a contrast image and a non-contrast image of the subject are registered in association with each other.

  The diagnostic device 30 has various types of information corresponding to key operations on the main body device 31, an image display device 32 that displays an image on the monitor 32 a according to an instruction from the main body device 31, and the main body device 31. An input keyboard 33 and a mouse 34 for inputting an instruction corresponding to, for example, an icon or the like displayed at that position by designating an arbitrary position on the monitor 32a are provided.

  When the user inputs the subject's name or identification number using the mouse 34 or the like of the diagnostic device 30, the input content is transmitted to the management server 20. The management server 20 acquires the name and identification number of the subject from the diagnostic device 30, and sends the contrast image, the non-contrast image, and the medical record associated with them to the diagnostic device 30. In the diagnostic device 30, by performing image processing on the contrast image and the non-contrast image, a bone removal image from which the bone in the contrast image has been removed is generated, and the contrast image and the bone removal image are displayed on the monitor 32a. The By confirming various medical images displayed on the monitor 32a of the diagnostic device 30, the user can diagnose the medical condition of the subject without causing external damage to the subject.

  The user looks at the medical image displayed on the monitor 32 a of the diagnostic device 30 to diagnose the medical condition of the subject, and edits the medical chart using the mouse 34 and the keyboard 33. The edited chart is sent to the management server 20, and the chart stored in the management server 20 is updated to a new chart sent from the diagnostic device 30.

  The medical diagnosis system shown in FIG. 1 is basically configured as described above.

  Here, the feature of the medical diagnosis system as an embodiment of the present invention is the processing content executed by the diagnostic apparatus 30. Hereinafter, the diagnostic device 30 will be described in detail.

  FIG. 2 is a hardware configuration diagram of the diagnostic device 30.

  As shown in FIG. 2, the main unit 31 of the diagnostic device 30 reads a program stored in the CPU 101 that executes various programs and the hard disk device 103 and develops the main memory for execution by the CPU 101. 102, a hard disk device 103 storing various programs and data, an FD (flexible disk) 41, an FD drive 104 accessing the FD 41, a CD-ROM drive 105 accessing the CD-ROM 42, and the management server 20 An I / O interface 106 that receives image data and the like and sends various instruction data to the management server 20 is built in. These various elements, and the image display device 32, keyboard 33, and mouse 34 shown in FIG. They are connected to each other via a bus 107.

  Here, the CD-ROM 42 stores an image display program 200 (see FIG. 3) for constructing an embodiment of the region determination device of the present invention in the diagnostic device 30.

  FIG. 3 is a conceptual diagram showing the CD-ROM 42.

  As shown in FIG. 3, the image display program 200 stored in the CD-ROM 42 includes an image acquisition unit 210, a first extraction unit 220, a first classification unit 230, a second extraction unit 240, a second classification unit 250, and a removal. The image generation unit 260 and the image display unit 270 are configured.

  The CD-ROM 42 is loaded into the CD-ROM drive 105 of the diagnostic device 30, and the image display program 200 stored in the CD-ROM 42 is uploaded to the diagnostic device 30 and stored in the hard disk device 103. Then, when the image display program 200 is activated and executed, a medical image display device 300 (see FIG. 4) having a function as one embodiment of the region determination device of the present invention is built in the diagnostic device 30. Is done.

  In the above, the CD-ROM 42 is exemplified as the storage medium for storing the image display program 200, but the storage medium for storing the image display program 200 is not limited to the CD-ROM, and other optical discs, It may be a storage medium such as MO, FD, or magnetic tape. Further, the image display program 200 may be directly supplied to the diagnostic apparatus 30 via the I / O interface 106 without using a storage medium.

  Details of each part of the image display program 200 will be described together with the operation of each part of the medical image display apparatus 300.

  FIG. 4 is a functional block diagram of the medical image display apparatus 300.

  The medical image display apparatus 300 includes an image acquisition unit 310, a first extraction unit 320, a first classification unit 330, a second classification unit 350, a second classification unit 350, a removed image generation unit 360, and an image display. The first extraction unit 320 includes a non-contrast extraction unit 321, a contrast extraction unit 322, and a position shift correction unit 323.

  An image acquisition unit 310, a first extraction unit 320, a first classification unit 330, a second extraction unit 340, a second classification unit 350, a removed image generation unit 360, which constitute the medical image display device 300, The image display unit 370 includes the image acquisition program 210, the first extraction unit 220, the first classification unit 230, the second extraction unit 240, the second classification unit 250, and the removed image generation unit that constitute the image display program 200 of FIG. 260 and the image display unit 270, respectively.

  Each element in FIG. 4 is composed of a combination of computer hardware and an OS or application program executed on the computer, whereas each element of the image display program 200 shown in FIG. The difference is that it is configured only by application programs.

  FIG. 5 shows a flow of a series of processing in the medical image display apparatus 300 shown in FIG. 4 until a contrast image and a non-contrast image are acquired from the management server 20 and a bone in the contrast image is extracted using the non-contrast image. FIG.

  Hereinafter, by describing the operation of each element of the medical image display apparatus 300 shown in FIG. 4 according to the flowchart of FIG. 5, each element of the image display program 200 shown in FIG.

  When the user inputs the name and identification number of the subject to be diagnosed using the mouse 34 and keyboard 33 shown in FIG. 1, the input contents are transmitted to the management server 20 via the I / O interface 106 of FIG. In the management server 20, when the name and identification number of the subject are acquired, the contrast image, the non-contrast image, and the medical record of the subject are sent to the diagnostic device 30.

  The contrast image and the non-contrast image sent from the management server 20 are acquired by the image acquisition unit 310 shown in FIG. 4 (step S1 in FIG. 5).

  FIG. 6 is a diagram illustrating an example of a contrast image and a non-contrast image sent from the management server 20.

  In the CT apparatus 12 shown in FIG. 1, each cross section when the subject P is cut from the chest to the base of the foot at a plurality of cutting positions X0 to Xn is photographed. In the present embodiment, the same subject P is photographed twice in succession using the CT apparatus 12 in each of the state in which no contrast medium is administered to the subject and the state in which the contrast agent is administered to the subject. A plurality of cross-sectional images at each of the plurality of cutting positions are generated. In part (A) of FIG. 6, there is a cross-sectional image 410 (hereinafter, this cross-sectional image 410 is referred to as a contrast image 410) in a state where a contrast agent is poured at one cutting position Xm among a plurality of cutting positions. In FIG. 6B, part (B) shows a cross-sectional image 410 ′ at the cutting position Xm in which no contrast agent is poured (hereinafter, this cross-sectional image 410 ′ is referred to as a non-contrast image 410 ′). It is shown. In practice, the image acquisition unit 310 acquires a plurality of cross-sectional images at each of a plurality of cutting positions. In the following, the contrast image 410 and the non-contrast image 410 ′ at one cutting position Xm are representative of them. To explain.

  In the contrast image 410 shown in part (A) of FIG. 6, in addition to the organs and blood vessels to be diagnosed, bones are also expressed at a high image density, and even if a lesion is present in the contrast image 410, There is a problem that it is difficult to see because it is hidden in the bone.

  The contrast image 410 and the non-contrast image 410 ′ acquired by the image acquisition unit 310 are transmitted to the first extraction unit 320, and the contrast image 410 is also transmitted to the second extraction unit 340 and the removal image generation unit 360. The image acquisition unit 310 corresponds to an example of a contrast image acquisition unit according to the present invention, and also corresponds to an example of a non-contrast image acquisition unit according to the present invention.

  The contrast image 410 transmitted to the first extraction unit 320 is acquired by the contrast extraction unit 322, and the non-contrast image 410 ′ is acquired by the non-contrast extraction unit 321.

  The contrast extraction unit 322 first determines the first threshold value and the second threshold value used for bone extraction based on the image density distribution of the contrast image 410 transmitted from the image acquisition unit 310.

  FIG. 7 is a graph showing the image density distribution of the contrast image 410.

  In FIG. 7, the horizontal axis is associated with the image density value, and the vertical axis is associated with the frequency. In the graph of FIG. 7, the image density value T1 at the end position of the frequency peak that appears first when searching for the peak from the maximum value side to the minimum value side of the image density value is determined as the first threshold, and the frequency that appears second. The image density value T2 at the peak start position is determined as the second threshold value. The range D1 between the start position and the end position of the frequency peak that appears first mainly includes the bone region, and the interval from the end position of the first peak to the start position of the second frequency peak that appears. The range D2 mainly includes a blood vessel region.

  Subsequently, in the contrast extraction unit 322, each region having an image density equal to or higher than the first threshold T1 is detected from the contrast image 410 illustrated in part (A) of FIG. Each candidate area estimated as a candidate is extracted. (Step S2_1 in FIG. 5).

  FIG. 8 is a diagram illustrating each candidate region extracted by the contrast extraction unit 322.

  The first contrast extracted image 421 shown in FIG. 8 is a plurality of candidate areas 51, 52, 53, 54, 55, 56, 57, 61, 62 extracted from the contrast image 410 shown in Part (A) of FIG. It is configured. In the contrast image 410 in which the subject is imaged with the contrast agent administered, the image density of some non-bone regions belonging to blood vessels, organs, and the like is high in addition to the bone regions belonging to bones. In the candidate areas 51, 52, 53, 54, 55, 56, 57, 61, and 62 having the above image density, it is estimated that a bone area and a non-bone area are mixed. The contrast extraction unit 322 transmits the first contrast extraction image 421 to the misalignment correction unit 323, transmits the first threshold T1 to the non-contrast extraction unit 321, and transmits the first threshold T1 and the second threshold T2 to the second extraction unit 340. Tell. The contrast extraction unit 322 corresponds to an example of a candidate area extraction unit according to the present invention.

  The non-contrast extraction unit 321 detects each region having an image density equal to or higher than the first threshold T1 from the non-contrast image 410 ′ shown in part (B) of FIG. A reference area serving as a reference for the extraction process is extracted.

  FIG. 9 is a diagram showing each reference region extracted by the non-contrast extraction unit 321. As shown in FIG.

  The non-contrast-extracted image 421 ′ shown in FIG. 9 includes a plurality of reference regions 51 ′, 52 ′, 53 ′, 54 ′, 55 ′, and 56 extracted from the non-contrast image 410 ′ shown in Part (B) of FIG. ', 57'. In the non-contrast image 410 ′ obtained by photographing the subject without administration of the contrast agent, the image density of the non-bone region excluding the bone region belonging to the bone of the subject is considerably low, and the reference region has an image density equal to or higher than the first threshold T1. 51 ′, 52 ′, 53 ′, 54 ′, 55 ′, 56 ′, 57 ′ are all estimated to be bone regions. The non-contrast extraction unit 321 transmits the non-contrast extraction image 421 ′ to the positional deviation correction unit 323. The non-contrast extraction unit 321 corresponds to an example of a reference region extraction unit according to the present invention.

  The positional deviation correction unit 323 corrects the positional deviation between the first contrast extraction image 421 transmitted from the contrast extraction unit 322 and the non-contrast extraction image 421 ′ transmitted from the non-contrast extraction unit 321. In the present embodiment, first, the rightmost points P1, Q1, the leftmost points P2, Q2, and the lowest points P3, Q3 are detected from the first contrast extraction image 421 and the non-contrast extraction image 421 ′, respectively. Subsequently, based on the relative position of each point detected from the first contrast extraction image 421 and the non-contrast extraction image 421 ′, the distance, rotation amount, and expansion / contraction between the first contrast extraction image 421 and the non-contrast extraction image 421 ′ The rate and the like are calculated, and the positional deviation between the first contrast extraction image 421 and the non-contrast extraction image 421 ′ is corrected using these parameters. As a technique for correcting a positional deviation between images, techniques such as an image matching process for correcting a positional deviation between a plurality of images and an ICP (Iterative Closest Point) have been widely known. Then, detailed description is abbreviate | omitted. The first contrast extraction image 421 and the non-contrast extraction image 421 ′ whose position deviation is corrected are transmitted to the first classification unit 330.

  Based on the non-contrast-extracted image 421 ′, the first classification unit 330 belongs to the candidate regions 51, 52, 53, 54, 55, 56, 57, 61, 62 in the first contrast-extracted image 421 to the bone. The bone region and the non-bone region other than the bone are classified (step S3 in FIG. 5). In the present embodiment, first, the non-contrast extraction image 422 is mapped on the first contrast extraction image 421, and the candidate regions 51, 52, 53, 54, 55, 56, 57, 61 in the first contrast extraction image 421 are mapped. , 62, a region that overlaps 80% or more with each of the reference regions 51 ′, 52 ′, 53 ′, 54 ′, 55 ′, 56 ′, 57 ′ in the non-contrast extraction image 421 ′ is classified as a bone region. Regions other than are classified as non-bone regions.

  FIG. 10 is a diagram illustrating an example of the first contrast extraction image 421 to which the non-contrast extraction image 421 ′ is mapped.

  In the example shown in FIG. 10, among the candidate regions 51, 52, 53, 54, 55, 56, 57, 61, and 62 in the first contrast extraction image 421, the region 51 that is expressed in white in FIG. 8. , 52, 53, 54, 55, 56, 57 overlap 80% or more with each reference region 51 ', 52', 53 ', 54', 55 ', 56', 57 'in the non-contrast-extracted image 421'. And is classified as a bone region. Of the candidate regions 51, 52, 53, 54, 55, 56, 57, 61, and 62 in the first contrast-extracted image 421, the regions 61 and 62 represented by dotted lines in FIG. It does not overlap with the extracted image 421 ′ and is classified as a non-bone region.

  Thus, by using a non-contrast image, a bone region in the contrast image can be easily extracted. In this embodiment, in order to extract the bone region in the contrast image 410 more precisely, the bone regions 51, 52, 53, 54, 55, 56, 57 already classified in the contrast image 410, and the non-bone Bone regions are also extracted from regions other than the regions 61 and 62. The classification result in the first classification unit 330 is transmitted to the second classification unit 350.

  The second extraction unit 340 uses a second threshold value lower than the first threshold value used in the first extraction unit 320 from the contrast image 410 shown in Part (A) of FIG. Each region having a density is extracted (step S2_2 in FIG. 5). The second extraction unit 340 corresponds to an example of a new candidate area extraction unit according to the present invention.

  FIG. 11 is a diagram illustrating each region extracted by the second extraction unit 340.

  The second contrast extraction image 422 shown in FIG. 11 includes bone regions 51, 52, 53, 54, 55, 56, 57 and non-bone regions 61, 62 that are also included in the first contrast extraction image 421 shown in FIG. In addition, candidate areas 71, 72, 75, 76, 77 surrounding each of these areas are included. At this time, the candidate area 72 in the center of the newly extracted candidate areas 71, 72, 75, 76, 77 includes the already classified bone areas 52, 53, 54 and the non-bone areas 61, 62. It is comprehensively surrounded. The second extraction unit 340 transmits the second contrast extraction image 422 to the second classification unit 350.

  The second classification unit 350 classifies the newly extracted candidate areas 71, 72, 75, and 76 into a bone area and a non-bone area.

  First, the classified bone regions 51, 52, 53, 54, 55, 56, 57 and the non-bone regions 61, 62 in the second contrast extraction image 422 are expanded by a predetermined size (step S4_2 in FIG. 5). . For example, when the size of the contrast image 410 is 512 pixels × 512 pixels, the extended size is preferably about 2 to 4 pixels.

  FIG. 12 is a diagram illustrating the second contrast extraction image 422 in which the classified region is expanded.

  In the second contrast-extracted image 422 shown in FIG. 12, the non-bone regions 61 and 62 shown in FIG. 11 are expanded to be combined into one non-bone region 60 and newly extracted candidate regions 71, 72, and 75. , 76, 77, the candidate regions 75, 76 surrounding the bone regions 55, 56 are absorbed by the expanded bone regions 55, 56, and the bone regions 52, 53, 54 and the non-bone regions 61, 62 are replaced with each other. Part of the candidate region 72 that has been encompassed is absorbed by the expanded bone regions 52, 53, 54 and the combined non-bone region 60.

  In the second contrast extraction image 422 shown in FIG. 12, the second classification unit 350 has already classified the bone regions 51, 52, 53, 54, and the remaining candidate regions 71, 72, and 77, respectively. Among the 55, 56, 57 and non-bone regions 60, the closest contact region is determined (step S5_2 in FIG. 5), and the classification of each of these candidate regions 71, 72, 77 is determined. Determine the same classification as the classification to which the contact area belongs. In this example, since the upper left candidate region 71 is in contact with the upper left bone region 51 most, it is determined to be a bone region, and the lower left candidate region 72 is in contact with the central non-bone region 60 most. Therefore, the upper right candidate region 75 is determined to be a bone region because it is in most contact with the upper right bone region 55.

  The hard disk device 103 shown in FIG. 2 stores an average distance from the body surface of the human body to the bone, and the second classification unit 350 is in contact with the bone area and the non-bone area with almost the same area. When there is a candidate area, if the distance from the body surface of the candidate area is close to a predetermined distance from the distance stored in the hard disk device 103, the candidate area is determined as a bone area.

  FIG. 13 is a diagram illustrating a second contrast extraction image 422 in which candidate areas are classified.

  As shown in FIG. 13, the newly extracted candidate areas 71, 72, 75, 76, and 77 shown in FIG. 11 are classified, so that the second contrast extracted image 422 becomes a new bone area 51, 52, 53, 54, 55, 56, 57 and non-bone region 60. In the present embodiment, each region satisfying a strict extraction condition (first threshold T1) is extracted from the contrast image 410, and each region is classified into a bone region and a non-bone region based on the non-contrast image 410 ′. Further, each region that satisfies the loose extraction condition (second threshold value T2) is extracted, and the newly extracted region is classified based on the contact relationship with the already classified region. Therefore, even if there is a bone region having an image density lower than the first threshold value T1, the bone region can be classified with high accuracy.

  Furthermore, the second extraction unit 340 uses a third threshold value lower than the second threshold value T2 from the contrast image 410 shown in part (A) of FIG. The candidate area is extracted (step S2_2 in FIG. 5), and the second classification unit 350 classifies each candidate area newly extracted by the second extraction unit 340 into a bone area and a non-bone area (step in FIG. 5). S4_3, S5_3).

  Thereafter, a threshold value as an extraction condition is lowered to extract a new candidate region (step S2_n in FIG. 5), and the new candidate region is classified into a bone region and a non-bone region (steps S4_n and S5_n in FIG. 5). A series of processing is repeated a predetermined number of times (for example, 5 times). By extracting the candidate area and the classification of the extracted candidate area multiple times in this way, the candidate area is extracted little by little, and only the area that should originally belong to the bone is classified into the bone area Therefore, the bone extraction accuracy is improved. A combination of the first classification unit 330 and the second classification unit 350 corresponds to an example of an area determination unit according to the present invention.

  As described above, the bone in the contrast image 410 is extracted. The extraction result of the bone is transmitted to the removed image generation unit 360.

  The removed image generation unit 360 removes the bone region transmitted from the second classification unit 350 from the contrast image 410 shown in Part (A) of FIG. 6 to generate a bone removal image. The generated bone removal image is transmitted to the image display unit 370 and displayed on the monitor 32a.

  FIG. 14 is a diagram showing an extracted bone image portion 423, and FIG. 15 is a diagram showing a cross-sectional image display screen 500 displayed on the monitor 32a.

  In the cross-sectional image display screen 500 shown in FIG. 15, in addition to the bone removal image 510, the name of the subject, the cutting position “Xm”, and the shooting date are also displayed. This bone removal image 510 is an image obtained by removing the bone image portion 423 shown in FIG. 14 from the contrast image 410 shown in part (A) of FIG. 6, and the user confirms the bone removal image 510 by The size and position of the lesion can be accurately recognized.

  Above, description of 1st Embodiment of this invention is complete | finished and 2nd Embodiment of this invention is described. Since the second embodiment of the present invention has substantially the same configuration as the first embodiment, the same components are denoted by the same reference numerals, description thereof will be omitted, and only the differences will be described.

  FIG. 16 is a functional block diagram of the medical image display apparatus 301 according to the second embodiment of the present invention.

  The medical image display apparatus 301 of the present embodiment has substantially the same configuration as the medical image display apparatus 300 of the first embodiment shown in FIG. 4, but the medical image display apparatus 301 of the present embodiment has the first configuration. The extraction unit 320 includes a positional deviation correction unit 323 and a difference image generation unit 324.

  When the contrast acquisition image 410 and the non-contrast image 410 ′ shown in FIG. 6 are acquired by the image acquisition unit 310, the position deviation correction unit 323 of the first extraction unit 320 acquires the positions of the contrast image 410 and the non-contrast image 410 ′. The deviation is corrected. The contrast image 410 and the non-contrast image 410 ′ after the positional deviation correction are transmitted to the difference image generation unit 324.

  In the difference image generation unit 324, a difference image between the contrast image 410 and the non-contrast image 410 ′ is generated. The generated difference image is transmitted to the first classification unit 330.

  In the first classification unit 330, a bone region is extracted from the contrast image 410 using the difference image transmitted from the difference image generation unit 324. In the contrast image 410 shown in Part (A) of FIG. 6, the image density of the bone region belonging to the bone and some non-bone regions belonging to the organs and blood vessels is high, and the non-contrast image shown in Part (B) of FIG. In the image 410 ′, the image density of the bone region is high. The first classification unit 330 classifies a region having a small difference value as a bone region and classifies a region having a large difference value as a non-bone region among the difference images generated by the difference image generation unit 324. The classification result in the first classification unit 330 is transmitted to the second classification unit 350.

  In the second extraction unit 340, in the same manner as in the first embodiment, each candidate region having an image density higher than a predetermined threshold value in the medical image transmitted from the image acquisition unit 310 is extracted. In the second classification unit 350, each candidate area is classified based on the degree of contact between each newly extracted candidate area and the already classified bone area and non-bone area.

  As described above, by using the difference image between the contrast image and the non-contrast image, the bone region in the contrast image can be easily determined.

  In the above description, the first threshold value and the second threshold value corresponding to an example of the extraction criterion according to the present invention are determined based on the image density distribution. However, the reference region extraction unit, the candidate region extraction unit, and the new threshold value according to the present invention are determined. The candidate area extraction unit may extract an area using extraction conditions set in advance. In contrast images, both bone and contrast blood have high image density, but a blood vessel wall having low image density exists between the bone and contrast blood. As the first threshold value T1, bone and contrast blood in the image are extracted, and a value (CT value of about 280 to 320) from which blood vessel walls, organs and lesions other than contrast blood are not extracted is applied. It is preferable to extract the blood and expand the bone region and the non-bone region until they reach the blood vessel wall using them as nuclei.

  In the above description, an example of extracting a bone from a medical image has been described. However, the region determination apparatus according to the present invention may determine a region belonging to a constituent part other than a bone from a medical image. It may be applied to the image of the subject.

1 is a schematic configuration diagram of a medical diagnosis system to which an embodiment of the present invention is applied. It is a hardware block diagram of a diagnostic apparatus. It is a conceptual diagram which shows CD-ROM. It is a functional block diagram of the medical image display apparatus which is 1st Embodiment of this invention. It is a flowchart figure which shows the flow of a series of processes until it acquires a medical image from a management server, and extracts the bone in the acquired medical image. It is a figure which shows an example of the contrast image and non-contrast image which are sent from the management server. It is a graph which shows distribution of the image density of a contrast image. It is a figure which shows each candidate area | region extracted by the contrast extraction part. It is a figure which shows each reference | standard area | region extracted by the non-contrast extraction part. It is a figure which shows an example of the 1st contrast extraction image to which the non-contrast extraction image was mapped. It is a figure which shows each area | region extracted by the 2nd extraction part. It is a figure which shows the 2nd contrast extraction image by which the classified area | region was expanded. It is a figure which shows the 2nd contrast extraction image by which the candidate area | region was classified. It is a figure which shows the image part of the extracted bone. It is a figure which shows the cross-sectional image display screen displayed on the monitor. It is a functional block diagram of the medical image display apparatus which is 2nd Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Image generation apparatus group 11 CR apparatus 12 CT apparatus 20 Management server 30 Diagnosis apparatus 31 Main body apparatus 32 Image display apparatus 33 Keyboard 34 Mouse 101 CPU
102 Main memory 103 Hard disk device 104 FD drive 105 CD-ROM drive 106 I / O interface 200 Image display program 210 Image acquisition unit 220 First extraction unit 230 First classification unit 240 Second extraction unit 250 Second classification unit 260 Removal image Generation unit 270 Image display unit 300, 301 Medical image display device 310 Image acquisition unit 320 First extraction unit 330 First classification unit 340 Second extraction unit 350 Second classification unit 360 Removal image generation unit 370 Image display unit

Claims (4)

A contrast image acquisition unit for acquiring a contrast image in which a subject is captured in a state in which a contrast medium is injected;
A non-contrast image acquisition unit for acquiring a non-contrast image in which the subject is captured in a state where no contrast agent is poured;
Wherein the non-contrast image, by using a predetermined first extraction criterion, a reference region extraction unit that extracts a reference region that belongs to configure site,
A candidate area extraction unit that extracts a candidate area from the contrast image using a predetermined second extraction criterion;
Of the candidate regions extracted by the candidate region extraction unit, a region that corresponds to the reference region extracted by the reference region extraction unit is determined as a region belonging to a predetermined component that constitutes the subject A confirmation section;
A new candidate area extraction unit that extracts a new candidate area that satisfies an extraction criterion that is looser than the second extraction criterion that is satisfied by a candidate area that has been confirmed as an area belonging to the component from the contrast image ;
The region determining unit uses a region that has already been determined to belong to the component part, and is a predetermined range of the determined region among regions that are formed from new candidate regions extracted by the new candidate region extracting unit. A region portion existing in the region is determined as a region belonging to the constituent part, and an undetermined region in the new candidate region is used by using an adjacent relationship between the undefined region in the new candidate region and the confirmed region. An area determination device for determining whether or not a determination area belongs to the component part.
2. The region determination apparatus according to claim 1, wherein the first extraction criterion and the second extraction criterion are the same type of extraction criterion. 2. The area determining apparatus according to claim 1, wherein the area determining unit determines an area belonging to the bone of the subject among the areas on the contrast image. The region according to claim 1, wherein the region determination unit determines a region corresponding to the reference region in consideration of a positional shift between the contrast image and the non-contrast image. Deterministic device.

Images