JP2000237185A - Medical image diagnosis supporting device and medical image diagnosis supporting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce an oversight of an abnormal shadow by a reader such as a doctor by displaying the supplementary information to the result of the abnormal candidate shadow detection process of a medical image. SOLUTION: The medical image data inputted to an input section 1 are stored in a data storage section 3, and the medical image data completely inputted to an abnormal candidate shadow detection process unit are judged by an input completion judgment section 2. An object image manual selection section 4 selects the medical image data specified by an operation section 11 among the completely inputted medical image data. An abnormal candidate detection section 5 reads the corresponding medical image data from the data storage section 3 and conducts an abnormal candidate shadow detection process. The detection process result is stored in the data storage section 3, and its supplementary information is stored in an supplementary information storage section 7 and is displayed on a display section 6 as required.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention automatically detects abnormal candidate shadows such as lung cancer candidate shadows from a medical image of a subject such as a patient, for example, a chest X-ray CT image. The present invention relates to a medical image diagnosis support apparatus and a medical image diagnosis support method that support interpretation by a doctor by presenting the same to a doctor or the like.

[0002]

2. Description of the Related Art Conventionally, a medical image diagnosis support apparatus, for example, C
In a T (computer image) lung cancer CAD (computer-aided diagnosis) apparatus, an abnormal candidate shadow (medical image) such as a lung cancer candidate shadow is obtained from a plurality of (for example, 30) medical images of a subject such as a patient to be examined. When a shadow that is determined to be abnormal on the image and is listed as a candidate) is detected by the automatic detection processing, only the detection processing result related to the medical image in which the abnormal candidate shadow is detected is displayed on the display screen. For this reason, the intermediate results of the abnormal candidate shadow detection processing (the lung field region graphic, the blood vessel region, the feature amount (size, circularity,
And the like) were not displayed on the display screen.

In addition, when abnormal candidate shadow detection processing is performed on one medical image of a plurality of medical images (for example, 30) of a subject, a large number of detection processing results can be obtained. Therefore, an upper limit is set on the number of detection areas on the medical image in the abnormal candidate shadow detection processing.

[0004]

However, for the following medical images in the above-mentioned conventional medical image diagnosis support apparatus, a doctor such as a doctor interprets an abnormal shadow without noticing the existence of the abnormal shadow. May be overlooked.

(1) A medical image for which no abnormal candidate shadow detection processing has been performed and the result of the detection processing has not been displayed.

(2) A medical image for which processing in the middle of abnormal candidate shadow detection processing, for example, extraction processing of an organ (lung field region or the like) has not been correctly performed.

(3) A medical image that exceeds the upper limit of the number of detection areas on the medical image in the abnormal candidate shadow detection processing.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and an object of the present invention is to display supplementary information on the detection processing result of an abnormal candidate shadow in a medical image, thereby displaying an abnormal shadow by an interpreter such as a doctor. An object of the present invention is to provide a medical image diagnosis support device and a medical image diagnosis support method capable of reducing oversight.

[0009]

According to a first aspect of the present invention, there is provided a detecting means for performing an abnormal candidate shadow detecting process on a medical image, and a detecting process performed by the detecting processing means. A medical image diagnosis support apparatus that includes a display unit that displays a result, and that assists diagnosis of a medical image, wherein the storage unit stores supplementary information of a detection processing result of the detection processing unit, and the storage unit stores the supplementary information. Instruction means for instructing the display means to display supplementary information.

In order to solve the above-mentioned problem, the invention according to claim 2 displays detection processing means for performing abnormal candidate shadow detection processing on a medical image, and displays a detection processing result of the detection processing means. In a medical image diagnosis support apparatus that includes a display unit and performs diagnosis support of a medical image, a storage unit that stores supplementary information of a detection processing result of the detection processing unit,
An instruction unit for instructing the display unit to display the supplementary information stored in the storage unit; and a graphic creation unit for converting the supplementary information into a graphic. The supplementary information is converted into a graphic by the graphic creating means and displayed on the display means.

[0011] In the medical image diagnosis support apparatus according to the first or second aspect of the invention, the invention according to the third aspect is configured such that the supplementary information stored in the storage means is detected in accordance with an instruction from the instruction means. The display means displays the result of the detection processing by the processing means at the same time.

[0012] In the medical image diagnosis support apparatus according to the first or second aspect of the present invention, the supplementary information stored in the storage means may include a supplementary information of the detected medical image. Number of sheets, information for specifying the detected medical image, information for specifying the medical image that has not been detected, the intermediate result of the detection processing, and the upper limit of the number of abnormal candidate shadow detection areas in the medical image Characterized in that it includes at least one piece of information indicating whether or not the number has been exceeded.

Further, in the medical image diagnosis support apparatus according to the present invention, the medical image is a chest X-ray CT image.

According to a sixth aspect of the present invention, there is provided a medical image processing apparatus for performing abnormal candidate shadow detection processing on a medical image, displaying the detection processing result, and supporting diagnosis of the medical image. In the diagnosis support method, the supplementary information of the detection processing result is stored, a display instruction to display the stored supplementary information is performed, and the supplementary information is displayed according to the display instruction.

According to another aspect of the present invention, an abnormal candidate shadow detection process is performed on a medical image, and the result of the detection process is displayed to support diagnosis of the medical image. In the medical image diagnosis support method, a supplementary information of the detection processing result is stored, a display instruction to display the stored supplementary information is performed, the supplementary information stored by the display instruction is made into a graphic, and the graphically made supplementary information is displayed. It is characterized by the following.

[0016] In the medical image diagnosis support apparatus according to the sixth or seventh aspect, the invention according to the eighth aspect is characterized in that the stored supplementary information is displayed simultaneously with the detection processing result in accordance with the display instruction. Features.

In the medical image diagnosis support apparatus according to the sixth or seventh aspect of the present invention, in the ninth aspect of the present invention, the stored supplementary information includes the number of detected medical images and the number of detected medical images. Information for specifying a medical image, information for specifying a medical image that has not been subjected to detection processing, an intermediate result of the detection processing, and whether the upper limit value of the number of abnormal candidate shadow detection areas in the medical image has been exceeded is indicated. It is characterized by including at least one piece of information.

Further, in the medical image diagnosis support apparatus according to the invention described in claim 6 or 7, the invention described in claim 10 is characterized in that the medical image is a chest X-ray CT image.

[0019]

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

In the embodiments of the present invention, a diagnosis support system which is a CAD (computer support diagnosis) system for a chest X-ray CT (computer tomography) image as a medical image will be described as an example.

(Embodiment 1) In the first embodiment of the present invention, abnormal candidate shadow detection processing is performed on a medical image to display the detection processing result and also display supplementary information thereof. I can do it.

FIG. 1 is a block diagram showing the configuration of a medical image diagnosis support apparatus according to the first embodiment of the present invention. The medical image diagnosis support apparatus according to the first embodiment of the present invention shown in FIG. 1 includes an input unit 1 to which medical image data such as chest X-ray CT image data is input, and an abnormal candidate shadow detection processing unit. An input completion determination unit 2 that determines whether a predetermined number of medical images have been input, a data storage unit 3 that stores medical image data and the like, and selection of medical image data to be subjected to abnormal candidate shadow detection processing, etc. A target image manual selection unit 4, an abnormal candidate detection unit 5 for performing an abnormal candidate shadow detection process on a medical image, and a display unit 6 for displaying a detection process result of the abnormal candidate shadow detection process on the medical image and its supplementary information And a supplementary information storage unit 7 for storing supplementary information of the detection processing result, and an operation unit 11 for giving an instruction of the abnormal candidate shadow detection processing. The input completion determination unit 2, the target image manual selection unit 4, and the abnormality candidate detection unit 5 constitute a control processing unit 20 including a CPU (Central Processing Unit) not shown.

When medical image data is input from a network, a magneto-optical disk drive, or the like (not shown), the input unit 1 stores the input medical image data in the data storage unit 3. The medical image data is added with medical image data collection conditions and patient identification information such as the patient name.

The data storage unit 3 is constituted by a hard disk drive (not shown) or the like, and stores medical image data input from the input unit 1, the detection result of the abnormal candidate shadow detection processing in the abnormal candidate detection unit 5, and the like.

The input completion judging section 2 selects, in the medical image data stored in the data storage section 3, the abnormal image candidate detection processing result which does not exist because the abnormal candidate shadow detection processing is not performed. The medical image data for which the input of the abnormal candidate shadow detection processing unit has been completed is determined, and data specifying information such as the data name of the medical image data for which the input has been completed is output to the target image manual selection unit 4.

The operation unit 11 is constituted by a keyboard, a mouse, and the like (not shown), and instructs the abnormal candidate detecting unit 5 to perform abnormal candidate shadow detection processing by an operation of an operator such as a doctor or a laboratory technician.

The target image manual selection unit 4 is a medical image data which is selected by the instruction from the operation unit 11 and is a medical image data to be subjected to the abnormal candidate shadow detection processing, among the data names of the medical image data output from the input completion determination unit 2. The data specifying information of the image data (unprocessed medical image data) is output to the abnormal candidate detecting unit 5.

The abnormal candidate detecting section 5 reads the corresponding unprocessed medical image data from the data storage section 3 based on the data specifying information output from the target image manual selecting section 4,
An abnormal candidate shadow detection process is performed on the read unprocessed medical image data. The detection processing result is stored in the data storage unit 3.
At the same time, the supplementary information of the detection processing result is stored in the supplementary information storage unit 7.

The supplementary information stored in the supplementary information storage unit 7 includes the number of medical images actually subjected to the abnormal candidate shadow detection processing, the upper limit value and the lower limit value of the slice position related to the detected medical image, and the detection processing. The slice identification number (ID) added to the missing medical image, the extraction result of a lung field contour or the like which is an intermediate result of the detection processing, and the number of detection areas on the detected medical image is a preset upper limit value (For example, 100), and excess mark blinking instruction information.

The display unit 6 includes a CRT (CRT) display, a liquid crystal display, a plasma display and the like (not shown), a graphical user interface (GUI) for displaying a patient selection list for selecting a patient, and a selected patient. The detection processing result of the medical image abnormal candidate shadow detection processing, supplementary information of the detection processing result, and the like are displayed.

The supplementary information storage unit 7 is constituted by a hard disk drive or the like (not shown),
Save the supplementary information of the result of the detection processing of the abnormal candidate shadow detection processing performed in step. The supplementary information is output to the display unit 6 as needed according to an instruction from the operation unit 11 by the operator or at the same time as the abnormal candidate shadow detection processing result.

Next, the operation of the medical image diagnosis support apparatus according to the first embodiment of the present invention will be described.

FIG. 2 is a flowchart showing a process for detecting an abnormal candidate shadow of a medical image in the medical image diagnosis support apparatus according to the first embodiment of the present invention. In FIG. 2, in step S1, medical image data is input to the input unit 1 at an arbitrary timing. In addition, together with the medical image data, patient identification information such as a medical image data collection condition and a patient name are input to the input unit 1. The input unit 1 stores the input medical image data and the like in the data storage unit 3. At this time, the file for storing the medical image data in the data storage unit 3 has information on the creation time of this file.

In step S2, the input completion determination unit 2 examines the medical image data stored in the data storage unit 3 at predetermined time intervals, and checks the medical image data that has not been subjected to the abnormal candidate shadow detection processing. Among them, medical image data for which input has been completed is determined in units of abnormal candidate shadow detection processing.

Here, chest X-ray C is used as medical image data.
The operation of the input completion determination unit 2 will be specifically described using a T image as an example.

FIG. 3 is a diagram for explaining a chest X-ray CT image subjected to abnormal candidate shadow detection processing in the medical image diagnosis support apparatus according to the first embodiment of the present invention. FIG.
As shown in the figure, the target image of the abnormal candidate shadow detection processing is 1
A series of chest X-ray CT images 10 of a human patient P
a to 10 g.

The abnormal candidate detecting section 5 performs a detecting process using these chest X-ray CT images 10a to 10g as a unit of the abnormal candidate shadow detecting process. When this detecting process is completed,
Information indicating that the chest X-ray CT image related to the patient P has been detected (detected information) is stored in the data storage unit 3.

Therefore, the input completion determination section 2 checks the detected processing information stored in the data storage section 3 and, based on the detected processing information, determines whether another abnormal candidate shadow detection processing has not been performed. A chest X-ray CT image of the patient is identified. Thereafter, whether or not the input of a series of chest X-ray CT images of another identified patient to the data storage unit 3 is determined as follows. Normally, a series of chest X-ray CT images of one patient are processed one by one by the input unit 1 and are continuously stored in the data storage unit 3.

That is, the input completion determination unit 2 determines the last input chest X-ray in a series of chest X-ray CT images of the same patient in the chest X-ray CT image data stored in the data storage unit 3. The file creation time of the line CT image is checked. If the determined file creation time is compared with the current time and a predetermined time has elapsed, it is determined that the input of a series of chest X-ray CT images of the patient has been completed. As a result, data identification information such as the data name of the chest X-ray CT image determined to have been completely input is output to the target image manual selection unit 4.

In step S3, the operation unit 1
By the operation of 1, the target image manual selection unit 4 causes the acquisition conditions associated with the medical image data and information indicating the processing status of the abnormal candidate shadow detection processing (unprocessed, processed, other (illegal end, non-target) ), The medical image data to be subjected to the detection processing performed by the abnormality candidate detection unit 5 is selected.

Incidentally, the abnormal candidate shadow detection processing is easily affected by the image quality of the medical image, and the detection processing result changes according to the image quality. Therefore, the operator checks the medical image acquisition conditions and displays a series of medical images of the patient that match the acquisition conditions of the target image for the abnormal candidate shadow detection processing.
Is operated in an interactive manner by operating the operation unit 11 on the display screen. FIG. 4 is a diagram showing a detection process manual selection mode displayed on the display screen of the display unit of the medical image diagnosis support apparatus according to the first embodiment of the present invention. In FIG. A patient b whose processing status is unprocessed,
This shows that the medical images related to f and g can be selected by the operator.

As described above, a medical image that does not match the medical image acquisition conditions (imaging and reconstruction conditions, number of images, etc.) for determining whether or not the image is a target image for abnormal candidate shadow detection processing is abnormal candidate shadow. Since the detection processing cannot be performed, the operator is notified of the fact that the detection processing could not be performed by displaying a list of the patient information related to such medical images (“not applicable”, “illegal termination”).

The conditions for collecting the medical images described above are as follows.

(1) Model of Medical Image Acquisition Apparatus The type of medical image acquisition apparatus such as an X-ray CT apparatus, a magnetic resonance imaging (MRI) apparatus, and the model name of the medical image acquisition apparatus. In addition, even if the medical image collection devices of the same type,
There are multiple different type names.

(2) Patient Position The patient is lying on his / her back, prone, etc.

(3) Names of Patient Sites for Collection of Medical Images Chest, head, abdomen, etc.

(4) Medical image collection direction A direction from the head to the foot, or a direction from the foot to the head.

(5) Types of Contrast Agent In an examination using an X-ray CT apparatus, there is a case where a contrast agent is injected into a patient's body to collect a medical image. In this case, the type of a contrast agent used.

(6) Presence or Absence of a Contrast Agent Whether or not a contrast agent was used at the time of data acquisition of an X-ray CT image as a medical image in an examination using an X-ray CT apparatus.

(7) Matrix Size of Medical Image The X-ray CT image obtained by the X-ray CT apparatus is composed of pixels having pixel values, and the number of pixels in the two-dimensional image. For example, it is constituted by 512 pixels vertically and 512 pixels horizontally.

(8) Pixel Size The size of one pixel constituting an X-ray CT image in an actual human body.

(9) Scanning method In X-ray CT image data collection by an X-ray CT apparatus, a normal scan mode in which the position of a bed on which a patient is placed is fixed and imaging is performed, and imaging is performed while moving the position of the bed There is a mode called helical scan.

(10) Moving speed of bed in helical scan The position of the bed that moves during one rotation of the X-ray tube of the X-ray CT apparatus.

(11) Image reconstruction function A function used to reconstruct an X-ray CT image.

(12) X-ray beam width The beam width of the X-ray beam emitted by the X-ray tube during data acquisition by the X-ray CT apparatus in the body axis direction of the patient.

(13) Tilt Angle of Gantry The tilt angle with respect to the moving direction of the bed in the orbit of the X-ray tube of the X-ray CT apparatus rotating.

(14) Tube voltage of X-ray tube Tube voltage of X-ray tube of X-ray CT apparatus.

(15) Amount of X-ray The amount of X-ray irradiated to the patient by the X-ray CT apparatus.

(16) Slice interval Position interval on the human body when reconstructing an X-ray CT image.

The operator operates the operation unit 11, and data identification information of a series of medical image data selected by the target image manual selection unit 4 is output to the abnormality candidate detection unit 5. on the other hand,
The input completion determination unit 2 adds information indicating that the medical image data is not a target of the detection processing and processed information to medical image data that is not a target of the abnormal candidate shadow detection processing, and stores the data in the data storage unit 3. .

In step S4, the abnormal candidate detecting section 5
In, the medical image data specified by the data specifying information output from the target image manual selection unit 4 is read from the data storage unit 3, and an abnormal candidate shadow detection process is performed on the read medical image data. . The outline of the abnormal candidate shadow detection processing is as follows.

(1) A lung field region is extracted from a medical image, for example, a chest X-ray CT image.

(2) Threshold processing is performed on the extracted lung field area to extract an area having a large pixel value.

(3) Calculate features such as circularity of the extracted area.

(4) An abnormal candidate shadow area is specified based on the calculated feature amount, and a center of gravity of the specified abnormal candidate shadow area is calculated.

The slice ID of the medical image in which the abnormal candidate shadow was detected, the number of abnormal candidate shadow areas for each medical image, the barycentric coordinates of each abnormal candidate shadow area, and the abnormal candidate shadow detection processing. The number of medical images subject to the detection and the detected information are stored in the data storage unit 3.
Is stored in

If a medical image data reading error or the like occurs during the abnormal candidate shadow detection processing, and the detection processing cannot be continued, and is abnormally terminated, it is determined that the medical image data has been illegally terminated. The information shown and the processed information are added and stored in the data storage unit 3.

Also, during the abnormal candidate shadow detection processing, if the medical image is excluded from the abnormal candidate shadow detection processing due to, for example, incorrect extraction of the lung field area, the medical image data is also included. On the other hand, information indicating that the data is not a target and processed information are added to the data storage unit 3.
Is stored in

The supplementary information of the abnormal candidate shadow detection processing result is output to the supplementary information storage unit 7 and stored in the supplementary information storage unit 7.

In step S 5, when a specific patient is selected from the patient selection list displayed on the display unit 6 by the operation unit 11, the target image manual selection unit 4 reads the patient's imaging conditions (abnormality) from the data storage unit 3. The acquisition conditions of the target image for the candidate shadow detection processing), the medical image data, and the detection processing result are read out and displayed on the display unit 6. Further, the supplementary information is read from the supplementary information storage unit 7 by the target image manual selection unit 4 and displayed on the display unit 6 as required by the operator's instruction from the operation unit 11 or simultaneously with the detection processing result or the like. Is done.

The operator operates the operation unit 11 to
By displaying the patient selection list and the imaging condition list of the patient on the display unit 6 and selecting the target image from the list, the abnormal candidate shadow detection processing can be performed on the selected target image.

FIG. 5 shows a patient selection list displayed on the display unit of the medical image diagnosis support apparatus according to the first embodiment of the present invention.
It is a figure which shows the example of the detection processing result of abnormal candidate shadow, and its supplementary information. In FIG. 5, the patient selection list 35, four slice images (slice Nos. 4, 10, 12, and 26) which are detection results of abnormal candidate shadows on the medical image relating to the patient C in the patient selection list 35 and their supplements An information list 36 is displayed, and lung field contours 31a, 31b, 31 which are intermediate results of the detection processing of each slice image are displayed.
The markers 30 and 31d indicate the positions of the abnormal candidate shadows.
a, 30b, 30c, and 30d are respectively attached. In addition, slice no. The twelve slice images show a feature amount (size S, circularity r) 32 which is an intermediate result of the detection process, and furthermore, an excess mark (dtc) indicating that the number of detection regions has exceeded the upper limit value. ) 33 are shown. Note that the upper limit is set in advance assuming that there is a large number of detection areas in one medical image, but the excess mark (dtc) 33 indicates that the number of detection areas exceeds the upper limit. In such a case, it is displayed blinking.

The patient selection list 35 includes, in addition to the patient name, information indicating that the medical image relating to the patient has been excluded from the processing and that the detection processing has been abnormally terminated (“not applicable”,
"Illegal termination") is shown as the detection processing result.

The supplementary information list 36 indicates the number of images (for example, 30) to be subjected to the abnormal candidate shadow detection processing, and the upper limit (for example, 3) and the lower limit (for example, 29) of the slice position of the detected medical image. Have been. Also, for example,
If there is a medical image that is excluded from the abnormal candidate shadow detection processing because the lung field area was not correctly extracted during the detection processing, the (unprocessed) slice ID of the medical image that was not detected is displayed in the supplementary information list. Shown at 36.

[0086] A patient selection list update button 37 for updating the patient selection list 35 is provided on the display screen of the display unit 6.

As described above, in the first embodiment of the present invention, an operator such as a doctor or a laboratory technician checks the medical image acquisition conditions, selects an image to be subjected to abnormal candidate shadow detection processing, and selects the image. An instruction for abnormal candidate shadow detection processing is given to the medical image obtained, (a) display of the number of medical images actually subjected to abnormal candidate shadow detection processing, and (b) identification of a medical image subjected to abnormal candidate shadow detection processing. (C) display of slice IDs of medical images for which abnormal candidate shadow detection processing has not been performed,
(D) The intermediate results of the abnormal candidate shadow detection processing, for example, the extraction results of the lung field region (the contours of the lungs, blood vessel shadows, characteristic amounts (circularity, density variance, size, etc.) of the lung cancer candidate shadows) Display superimposed on the detection processing result, (e) blinking display of a mark indicating that the number of detection regions on the medical image has exceeded the upper limit value, and the like are performed. As a result, 1) a medical image in which the detection processing result is not displayed because the detection processing is not performed; 2)
In the middle of the detection process, for example, a medical image in which the extraction of an organ (pulmonary region or the like) is not correctly performed, 3) supplementary information for prompting re-reading of a medical image exceeding the upper limit of the number of detection regions is displayed. Therefore, it is possible to reduce the possibility that a reader such as a doctor overlooks an abnormal shadow.

(Embodiment 2) In a second embodiment of the present invention, there is provided a medical image diagnosis support apparatus having substantially the same configuration as the medical image diagnosis support apparatus of the first embodiment of the present invention. A target image automatic selection unit for automatically selecting a medical image to be subjected to abnormal candidate shadow detection processing, and a graphic generation unit for displaying supplementary information of the detection processing result in a graphic form.

FIG. 6 is a block diagram showing the configuration of a medical image diagnosis support apparatus according to the second embodiment of the present invention. In the medical image diagnosis support apparatus according to the second embodiment of the present invention shown in FIG. 6, the target image automatic selection unit 8 has a table 8a for storing medical image acquisition conditions in advance, and completes input. Among the data specifying information of the medical image data output from the determination unit 2, the data specifying information of the medical image data collected based on the collecting condition that matches the collecting condition of the medical image stored in the table 8a in advance is used. It is output to the abnormal candidate detection unit 5 as being a target of abnormal candidate shadow detection processing.

The abnormal candidate detecting section 5 reads out the medical image data specified by the data specifying information output from the target image automatic selecting section 8 from the data storage section 3, performs an abnormal candidate shadow detecting process, and executes the detecting process result. Is stored in the data storage unit 3, and at the same time, supplementary information of the detection processing result is stored in the supplementary information storage unit 7.

Thereafter, when a specific patient is selected from the patient selection list displayed on the display unit 6 by the operation unit 11, the patient's imaging conditions and medical image data are read from the data storage unit 3 by the target image manual selection unit 4. , And the detection processing result are read out and displayed on the display unit 6. Also,
The supplementary information is read from the supplementary information storage unit 7 by the target image manual selection unit 4 as required by the operator's instruction from the operation unit 11 or simultaneously with the detection processing result and the like. As shown in FIG. 7, the image is converted into a graphic (computer graphics, CG) and displayed on the display unit 6. Thereby, supplementary information (processing range, unprocessed slice No., processing target number, etc.) of the detection processing result can be more easily grasped.

Although the embodiments of the present invention have been described above, the present invention is not limited to the first and second embodiments, and various modifications can be made within the scope of the present invention. .

[0082]

As described above, according to the present invention, (a) display of the number of medical images actually subjected to abnormal candidate shadow detection processing;
(B) display of information (upper limit value and lower limit value of slice position) for specifying a medical image subjected to abnormal candidate shadow detection processing, and (c) display of a slice ID of a medical image not subjected to abnormal candidate shadow detection processing. And (d) the abnormal candidate shadow detection process, for example, the extraction results of lung field regions (lung contours, blood vessel shadows, characteristic amounts (circularity, density variance, size, etc.) of lung cancer candidate shadows) are used as abnormal candidate shadows. Display superimposed on the detection processing result of
(E) A mark indicating that the number of detection areas on the medical image has exceeded the upper limit value is blinked or the like. As a result, 1) it can be grasped whether the abnormal candidate shadow detection processing has been performed on the expected number of medical images, 2) it can be grasped whether the detection processing has been performed within the expected detection processing range, and 3) the detection can be performed. The medical image that has not been processed can be grasped, and 4) the intermediate result of the detection process can be grasped, so that the validity of the detection process can be confirmed. 5) The number of detection areas exceeds a preset limit. I can understand. Therefore, it is possible to reduce oversight of abnormal shadows by an interpreter such as a doctor, and it is possible to improve diagnostic image diagnosis support.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a medical image diagnosis support apparatus according to a first embodiment of this invention.

FIG. 2 is a flowchart showing abnormal candidate shadow detection processing of a medical image in the medical image diagnosis support apparatus according to the first embodiment of the present invention.

FIG. 3 is a chest X-ray CT subjected to abnormal candidate shadow detection processing in the medical image diagnosis support apparatus according to the first embodiment of the present invention.
It is a figure for explaining an image.

FIG. 4 is a diagram illustrating a detection process manual selection mode displayed on a display unit of the medical image diagnosis support apparatus according to the first embodiment of the present invention.

FIG. 5 is a diagram illustrating an example of a patient selection list, abnormal candidate shadow detection processing result, and supplementary information thereof displayed on the display unit of the medical image diagnosis support apparatus according to the first embodiment of the present invention.

FIG. 6 is a block diagram showing a configuration of a medical image diagnosis support device according to a second embodiment of the present invention.

FIG. 7 is a diagram illustrating a display example of supplementary information graphically formed by a graphic creation unit of the medical image diagnosis support apparatus according to the second embodiment of the present invention.

[Explanation of symbols]

 P Subject 1 Input unit 2 Input completion determination unit 3 Data storage unit 4 Target image manual selection unit 5 Abnormal candidate detection unit 6 Display unit 7 Supplementary information storage unit 8 Target image automatic selection unit 9 Graphic creation unit 10a to 10g Chest X-ray CT image 11 Operation unit 20 Control processing unit

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Taihei Kondo 1385-1 Shimoishigami, Otawara City, Tochigi Pref. Toshiba Nasu Factory Co., Ltd. (72) Inventor Takehiro Ema 2-16-4 Akabane, Kita-ku, Tokyo Toshiba F-term (reference) in Medical System Engineering Co., Ltd. 4C093 AA22 AA26 CA50 DA03 FB09 FB10 FB12 FF21 FF28 FF50 FG13 FH06 FH07

Claims (10)

[Claims] 1. A medical image diagnosis support system comprising: a detection processing unit configured to perform an abnormal candidate shadow detection process on a medical image; and a display unit configured to display a detection processing result of the detection processing unit. In the apparatus, there is provided a storage unit for storing supplementary information of a detection processing result of the detection processing unit, and an instruction unit for giving an instruction to display the supplementary information stored in the storage unit on the display unit. A medical image diagnosis support apparatus characterized by the above-mentioned. 2. A medical image diagnosis support system comprising: a detection processing unit for performing abnormal candidate shadow detection processing on a medical image; and a display unit for displaying a detection processing result of the detection processing unit; In the apparatus, storage means for storing supplementary information of the detection processing result of the detection processing means, instruction means for giving an instruction to display the supplementary information stored in the storage means on the display means, and the supplementary information A medical image diagnosis support apparatus, comprising: a graphic generating means for converting the supplementary information stored in the storing means by the instruction means into a graphic by the graphic generating means and displaying the supplementary information on the display means. . 3. The display unit according to claim 1, wherein the supplementary information stored in the storage unit is displayed on the display unit simultaneously with a detection processing result of the detection processing unit in accordance with an instruction from the instruction unit. 3. The medical image diagnosis support device according to 1. 4. The supplementary information stored in the storage unit includes information on the number of detected medical images, information for specifying the detected medical images, and specifying the undetected medical images. 3. The method according to claim 1, further comprising at least one of the following information: an intermediate result of the detection processing; and information indicating whether or not the upper limit of the number of abnormal candidate shadow detection areas in the medical image has been exceeded. Medical image diagnosis support device. 5. The medical image diagnosis support apparatus according to claim 1, wherein the medical image is a chest X-ray CT image. 6. A medical image diagnosis support method for performing abnormal candidate shadow detection processing on a medical image and displaying the detection processing result to support diagnosis of the medical image, wherein supplementary information of the detection processing result is stored. Providing a display instruction to display the stored supplementary information, and displaying the supplementary information according to the display instruction. 7. A medical image diagnosis support method for performing abnormal candidate shadow detection processing on a medical image, displaying the detection processing result, and supporting diagnosis of the medical image, wherein supplementary information of the detection processing result is stored. Providing a display instruction to display the stored supplementary information; converting the stored supplemental information into a graphic according to the display instruction; and displaying the graphicized supplementary information. 8. The medical image diagnosis support method according to claim 6, wherein the stored supplementary information is displayed simultaneously with the detection processing result according to the display instruction. 9. The stored supplementary information includes the number of detected medical images, information for specifying a medical image that has been detected, information for specifying a medical image that has not been detected, and information for detecting a medical image. 8. The medical image diagnosis support method according to claim 6, further comprising at least one of an intermediate result and information indicating whether or not the number of abnormal candidate shadow detection areas in the medical image exceeds an upper limit value. 10. The medical image diagnosis support method according to claim 6, wherein the medical image is a chest X-ray CT image.