JP5501491B2 - Diagnosis support apparatus and control method - Google Patents

Description

  The present invention relates to a medical diagnosis support system that can be used to improve diagnosis efficiency of medical examination data of a doctor by comparing and contrasting a plurality of pieces of diagnosis support information such as a doctor's findings and computer analysis on medical examination data such as a medical image.

In the medical field, digitization of medical images taken of patients has been realized. This kind of medical image data
・ CR (Computed Radiography) equipment,
-CT (Computed Tomography) equipment,
・ MRI (Magnetic Resonance Imaging) equipment,
Generated by an ultrasonic device (US; Ultrasound System) or the like. At the time of diagnosis, the generated medical image data is displayed on a monitor, and the medical image displayed on the monitor is read by a doctor as a user to observe the state of a lesioned part and a change with time.

  A medical image processing apparatus called a computer-aided diagnosis apparatus (CAD) has been developed for the purpose of reducing the burden on interpretation by such doctors. The medical image processing apparatus automatically detects a lesion as an abnormal shadow candidate by performing image analysis on the medical image data. This abnormal shadow detection process is a process for detecting an abnormal shadow candidate such as an abnormal tumor shadow representing cancer or a high-density microcalcification shadow using an electronic computer based on image data representing a radiographic image. . Thereby, it is possible to reduce the burden on the doctor's interpretation and improve the accuracy of the interpretation result.

  Usually, when such CAD is used in an actual clinical site, a doctor interprets the image first, and then the doctor refers to the diagnosis support information output by the CAD and compares it with the result of his / her interpretation. . Specifically, in this work, the doctor associates the interpretation information of the interpretation result written by himself with the diagnosis support information calculated by CAD, and finds an oversight, a false detection, a difference in findings, etc. . At this time, by automatically comparing the interpretation report created by the doctor with the diagnosis support information calculated by CAD and presenting the difference, the workload of the doctor can be reduced (Patent Document 1).

Japanese Patent No. 3085724

  However, the difference between the interpretation report and CAD-calculated diagnosis support information includes a medically important difference regarding diagnosis and a difference that is not medically important such as wording and details of explanation on the interpretation report. . In Patent Document 1, since these differences in medical importance are not taken into account, a difference detection result that is not medically important is also presented to the doctor, and the doctor may be bothered as a result. was there. In addition, medically important difference information is buried in other information, and CAD diagnosis support information may not be effectively presented to a doctor.

  The present invention has been made in view of the above problems, and provides a suitable display of a comparison result between a result of interpretation by a doctor who is a user and diagnosis support information by CAD, thereby enabling interpretation work by a doctor or the like. The purpose is to improve the efficiency.

A diagnosis support apparatus according to an aspect of the present invention for solving the above-described problems has the following configuration. That is,
Detecting means for detecting a difference between first medical information acquired from information created by a user and second medical information obtained by computer processing for medical information;
Control means for displaying the difference on a display unit in a display form corresponding to a combination of a lesion name included in the first medical information and a lesion name included in the second medical information.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to provide the suitable display of the comparison result of the interpretation result by the doctor who is a user, and the diagnostic assistance information by CAD, and the efficiency of the interpretation work by a doctor etc. can be improved. .

It is a block diagram which shows the apparatus structural example of the medical diagnosis assistance apparatus which concerns on 1st Embodiment. It is a functional block diagram which shows the function structural example of the medical diagnosis assistance apparatus 1 which concerns on 1st Embodiment. It is a flowchart which shows the process sequence of the medical diagnosis assistance apparatus which concerns on 1st Embodiment. It is a figure explaining the process of the interpretation report analysis part. It is a figure explaining the process of the difference detection part. It is a figure explaining the process of the difference detection part. It is a figure explaining the process of the difference detection part. It is a figure which shows the data structural example of the importance rank information in the term importance dictionary 150. It is a figure which shows the example of a display of the processing result by a difference presentation part.

  Hereinafter, preferred embodiments of a medical diagnosis support apparatus and method according to the present invention will be described in detail with reference to the accompanying drawings. However, the scope of the present invention is not limited to the illustration by the following embodiment.

[First Embodiment]
{Hardware configuration}
First, the configuration of a medical diagnosis support apparatus for supporting a doctor's diagnosis based on medical examination data according to the first embodiment will be described. FIG. 1 is a block diagram illustrating a configuration example of a device according to the first embodiment. The medical diagnosis support apparatus 1 in FIG. 1 includes a central processing unit (CPU) 100, a main memory 101, a magnetic disk 102, a display memory 103, a monitor 104, a mouse 105, and a keyboard 106.

  As shown in FIG. 1, the medical diagnosis support apparatus 1 includes a medical image photographing apparatus 2 capable of photographing an image of a subject, such as an X-ray CT apparatus, an MR apparatus, a US apparatus, an X-ray apparatus, and a nuclear medicine apparatus. It may be connected. The medical diagnosis support apparatus 1 may be connected to a database 3 that stores medical examination data captured by the medical image capturing apparatus 2 and medical examination data including information necessary for diagnosis support processing. As shown in FIG. 1, these devices may be connected to each other via a network such as a local area network (LAN) 4 or may be directly connected by a dedicated interface.

  The CPU 100 mainly controls the operation of each component of the medical diagnosis support apparatus 1. The main memory 101 stores a control program executed by the CPU 100 or provides a work area when the CPU 100 executes the program. The magnetic disk 102 stores an operating system (OS), device drives for peripheral devices, various application software including a program for performing diagnosis support processing, which will be described later, and the like. The display memory 103 temporarily stores display data for the monitor 104. The monitor 104 is, for example, a CRT monitor or a liquid crystal monitor, and displays an image based on data from the display memory 103. The mouse 105 and the keyboard 106 are used by the user for pointing input and character input, respectively. The above components are connected to each other by a common bus 107.

  In this embodiment, the medical diagnosis support apparatus 1 reads a medical image or the like from the database 3 via the LAN 4. However, the present invention is not limited to this, and a storage device such as an FDD, a CD-RW drive, an MO drive, a ZIP drive, or the like may be connected to the medical diagnosis support apparatus 1 and medical images may be read from these drives. Alternatively, a medical image or the like may be acquired directly from the medical image photographing apparatus 2 via the LAN 4.

{Function structure}
Next, the functional configuration of the medical diagnosis support apparatus 1 according to the present embodiment will be described with reference to FIG. FIG. 2 is a functional block diagram of the medical diagnosis support apparatus 1 in the present embodiment. As shown in FIG. 2, the medical diagnosis support apparatus 1 includes an interpretation report input unit 10, an interpretation report analysis unit 11, a medical examination data input unit 12, a diagnosis support information generation unit 13, a difference detection unit 14, and a medical importance calculation unit. 15 and a difference presentation unit 16. Each unit described above is realized by the CPU 100 of the medical diagnosis support apparatus 1 executing a computer program stored in the main memory 101 and cooperating with the hardware of the medical diagnosis support apparatus 1. Hereinafter, each functional unit will be described.

<Interpretation Report Input Unit 10>
The interpretation report input unit 10 inputs interpretation report information, which is a result of interpretation by a doctor as a user, to the medical diagnosis support apparatus 1 based on medical examination data.

-Input via storage medium-network For example, the interpretation report input unit 10 is configured to be able to receive data via a network from a database recording interpretation report information created by a doctor who has performed interpretation. Can do. The data may be read from various storage media such as a FDD, a CD-RW drive, an MO drive, and a ZIP drive connected to the medical diagnosis support apparatus 1.

-Computer free sentence input Moreover, the interpretation report input part 10 may be comprised so that the doctor who performed interpretation can directly input the interpretation report information as an interpretation result into a computer with a keyboard, a mouse, etc.

・ Standard format The interpretation report input unit 10 prepares a standard format and options for contents to be entered in each item in the format in advance, and the doctor who performed the interpretation selects from the options, so that the interpretation report is generated. You may make it the structure produced | generated.

・ Optical Character Recognition (OCR)
The interpretation report input unit 10 may be configured by connecting a paper surface reading device such as a paper scanner and an optical character recognition device. According to this configuration, interpretation report information in a format that can be edited by a computer is generated by reading a handwritten sentence by a doctor who has performed interpretation with a scanner and performing OCR processing.

<Interpretation Report Analysis Unit 11>
The interpretation report analysis unit 11 analyzes the interpretation report information as an interpretation result by the doctor input by the interpretation report input unit 10 and analyzes the medical meaning.

  For example, as shown in FIG. 2, the interpretation report analysis unit 11 includes a morphological analysis unit 110, a class identification unit 112, and a meaning identification unit 114, and holds a structuring dictionary 111 and a medical thesaurus dictionary 113.

  First, the morphological analysis unit 110 divides the interpretation report information described in the natural sentence input from the interpretation report input unit 10 into words (morphemes). The structuring dictionary 111 is a dictionary in which medical-related words and classes are registered. The type of class registered in the structuring dictionary 111 is not limited. For example, “part”, “symptom”, “disease name”, and the like can be registered as appropriate. The class identifying unit 112 refers to the structuring dictionary 111, identifies the class of each word obtained by the morpheme analyzing unit 110, and generates structured data of interpretation report information. The structured data is structured data including elements having medical attributes such as “part”, “symptom”, and “disease name”.

  In the medical thesaurus dictionary 113, words are systematized based on the hierarchical relationship of concepts by an ontology that describes information on relationships between medical words. That is, in the medical thesaurus dictionary 113, a conceptually higher word (higher word) is positioned higher in the hierarchical structure, and a conceptually lower word (lower word) is positioned lower in the hierarchical structure. Words are organized hierarchically. The meaning specifying unit 114 refers to the medical thesaurus dictionary 113 and determines a thesaurus code that represents the hierarchical position of the content (word) of the element having the attribute “part” included in the structured data of the interpretation report. Details of specific processing using these configurations will be described later.

  Further, in the case of another configuration in which the interpretation report input unit 10 selects and inputs a word from options, morphological analysis becomes unnecessary. In this case, the interpretation report analysis unit 11 can also be configured by connecting a thesaurus dictionary relating to words prepared as options in advance in the interpretation report input unit 10 and means for collating the dictionary.

<Medical examination data input unit 12>
The medical examination data input unit 12 inputs medical examination data to the medical diagnosis support apparatus 1.

Example of Connection with LAN, CD-ROM, etc. The medical examination data input unit 12 has a configuration capable of receiving data via a LAN from a database that stores captured medical image data. The medical examination data input unit 12 is configured to be able to read medical image data from various storage media such as a FDD, CD-RW drive, MO drive, and ZIP drive connected to the medical diagnosis support apparatus 1. There may be.

-Example of connection with imaging apparatus The medical examination data input unit 12 is a medical image imaging apparatus capable of imaging an image of a subject, such as an X-ray CT apparatus, MR apparatus, US apparatus, X-ray apparatus, nuclear medicine apparatus, etc. The medical image data can be directly input from these devices.

An example of handling medical record information The medical examination data input unit 12 is not limited to inputting medical image data, but can input medical examination data including past and present interpretation reports, information necessary for diagnosis support processing, and the like. A possible configuration may be used. In that case, the configuration may be such that these data can be directly input by the user, or can be read from various storage media such as FDD, CD-RW drive, MO drive, and ZIP drive in which information is recorded. There may be. Further, it may be configured such that it can be connected to a database for recording these data via a LAN and can be received.

<Diagnosis support information generation unit 13>
The diagnosis support information generation unit 13 generates medical diagnosis support information related to the subject based on the medical examination data input by the medical examination data input unit 12. Details of specific processing relating to the diagnosis support information generation unit 13 will be described in detail later.

<Difference detection unit 14>
The difference detection unit 14 detects a difference between the medical meaning of the interpretation result obtained by the doctor extracted by the analysis by the interpretation report analysis unit 11 and the diagnosis support information generated by the diagnosis support information generation unit 13.

<Medical Importance Calculation Unit 15>
The medical importance calculation unit 15 calculates the medical importance of the difference between the doctor's interpretation result detected by the difference detection unit 14 and the diagnosis support information.

  For example, as shown in FIG. 2, the medical importance calculation unit 15 includes a term importance dictionary 150 and a collation unit 151, and has a medical importance according to the content of the difference detected by the difference detection unit 14. Degree can be obtained. At this time, the medical importance calculation unit 15 may be connected to the interpretation report analysis unit 11 and the diagnosis support information generation unit 13 to calculate the medical importance based on the processing results. The term importance dictionary 150 has data defining the medical importance of the words described in the interpretation report. Further, the collating unit 151 collates / searches a word that matches the difference information detected by the difference detecting unit 14 from the term importance dictionary 150, and determines its importance. Details of specific processing using these functional configurations will be described later.

<Difference presentation unit 16>
The difference presentation unit 16 adds the difference information detected by the difference detection unit 14 to the medical importance level calculated by the medical importance level calculation unit 15 on the interpretation result by the doctor input by the interpretation report input unit 10. The display form is changed and presented on the monitor 104.

{Description of processing}
Next, a specific processing procedure executed by the medical diagnosis support apparatus 1 of the present embodiment will be described with reference to the flowchart of FIG.

(Step S1)
The interpretation report input unit 10 inputs an interpretation report (interpretation report information) written by the doctor who performed the interpretation.

(Step S2)
Next, the interpretation report analysis unit 11 analyzes the interpretation report information input in step S1, and extracts the medical meaning included in the interpretation report information. A specific example of the process in step S2 will be described with reference to FIG. In FIG. 4, the interpretation report information 200 written by the doctor is an example of the interpretation report information input in step S1. Here, the interpretation report information entered as a free sentence by the doctor is shown as an example. First, the interpretation report analysis unit 11 performs morphological analysis on the interpretation report information 200 written by the doctor, thereby performing decomposition in units of words to obtain word decomposition result information 201. Next, the interpretation report analysis unit 11 collates each word of the word decomposition result information 201 with the structuring dictionary 111 so that each word is “part”, “symptom”, “disease name”, etc. Identify which of the classes corresponds to. Next, the interpretation report analysis unit 11 identifies each word whose class is specified by collating the meaning of the word with a medical thesaurus dictionary, and includes analysis including itemized medical meaning information. Result information 202 is generated. As described above, in step S2, the interpretation report information created by the doctor who is the user is analyzed, and analysis result information in which medical information extracted from the interpretation report information is associated with the item is generated.

(Step S3)
The medical examination data input unit 12 inputs medical examination data including medical image data.

(Step S4)
The diagnosis support information generation unit 13 generates medical diagnosis information suspected for the subject based on the medical examination data input in step S3. That is, diagnosis support information is generated by computer processing of medical examination data.

・ CAD that handles only medical image data
At this time, when medical image data is included in the medical examination data input in step S3, the diagnosis support information generation unit 13 first performs image processing for detecting a lesion candidate based on the image feature in the medical image data. . Next, discrimination processing for discriminating the authenticity and the lesion type is performed on the detected lesion candidate, and diagnosis support information for medical examination data is generated based on the result. In addition, since the process which produces | generates diagnostic assistance information from the medical examination data containing medical image data is known, detailed description is abbreviate | omitted.

・ CAD that handles information other than medical image data
Further, the processing target of the diagnosis support information generation unit 13 is not limited to medical image data, for example, medical examination data including past interpretation reports and medical records relating to the examinee, and other information that can be used for diagnosis support processing, etc. Can also be processed. In this case, medical diagnosis support information based on medical examination data other than the image information of the examinee can be generated. In addition, since the process which produces | generates diagnostic assistance information from the medical examination data containing medical image data is known, detailed description is abbreviate | omitted.

(Step S5)
The difference detection unit 14 detects a difference between the analysis result information 202 extracted and generated from the interpretation report information that is the interpretation result by the doctor in step S2 and the diagnosis support information generated in step S4.

  A specific example of the process in step S5 will be described with reference to FIG. In FIG. 5, the interpretation report analysis result information 300 corresponds to the analysis result information 202 representing the medical meaning of the interpretation report generated by the interpretation report analysis unit 11 in step S2. The diagnosis support information 301 is diagnosis support information generated by the diagnosis support information generation unit 13 in step S4. The interpretation report analysis result information 300 and the diagnosis support information 301 are each composed of itemized medically meaningful information. Therefore, the difference detection unit 14 detects the presence / absence of the difference and the content of each item as shown in the difference detection result information 302 by comparing the information for each item. Thus, the difference between each item is detected by comparing the diagnosis support information in which medical information obtained by computer processing of medical examination data is associated with the item and the analysis result information obtained by analyzing the interpretation report information. Is done.

  A specific example of the process in step S5 when the information of the interpretation result by the doctor extracted in step S2 and / or the diagnosis support information generated in step S4 includes a plurality of findings information will be described with reference to FIG. To do.

  In FIG. 6, the interpretation report analysis result information 400 corresponds to the interpretation report analysis result information 202 generated by the interpretation report analysis unit 11 in step S2. The diagnosis support information 401 and the diagnosis support information 402 are a plurality of pieces of diagnosis support information regarding different parts generated by the diagnosis support information generation unit 13 in step S4.

  In detecting the difference, first, it is checked whether or not the findings corresponding to the analysis result information 400 of the interpretation report exist in the diagnosis support information 401 and the diagnosis support information 402. Here, as an example, a method for examining the correspondence of findings based on “part” information will be described. In the analysis result information 400 of the interpretation report, “lower right leaf” is extracted as information of “part”. On the other hand, in the diagnosis support information 401 and the diagnosis support information 402, “lower right lobe (S1)” and “lower left lobe (S2)” are obtained. From these part information, it is determined that the diagnosis support information 401 having the same information on the item “part” corresponds to the analysis result information 400 of the interpretation report. Next, the difference detection unit 14 compares the associated findings information (in this example, the analysis result information 400 and the diagnosis support information 401) by the same method as described above to obtain the difference detection result information 403. The difference detection result information 403 shows an example in the case where it is obtained from the detection result that there is no difference between the findings information of both. Also, regarding the diagnosis support information 402 that could not be matched with the analysis result information 400 of the interpretation report, all of the information becomes difference information. The difference information included as is detected. The dimension is “15 mm” in the analysis result information 400, whereas the dimension is “15.3 mm” in the diagnosis support information 401. However, although there is a difference between the numerical accuracy (number of digits) calculated by the computer and the numerical accuracy (number of digits) when the interpretation doctor fills in, the difference detection unit 14 indicates that the meanings are equivalent. Since it is determined, it is determined that there is no difference. Thus, the difference may be detected by absorbing the difference in accuracy.

(Step S6)
Next, the medical importance calculation unit 15 determines whether or not there is a difference detected in step S5. If there is a difference, the process proceeds to step S7, and if there is no difference, the present process is terminated.

(Step S7)
The medical importance calculation unit 15 calculates and determines the medical importance of the difference detection information indicating the difference between the analysis result information of the interpretation result of the doctor detected in step S5 and the diagnosis support information. That is, the importance is determined for the difference for each item detected in step S5.

  The specific processing content of step S7 will be described in detail with reference to FIGS. Although various methods can be considered for calculating the medical importance in step S7, in this embodiment, the importance rank is assigned in advance according to the relationship to the life of the examinee for each lesion name. The case where the importance is determined using this will be described as an example.

Consider a case where analysis result information 500 and 501 of an interpretation report is obtained in step S2 and diagnosis support information 502 and 503 is obtained in step S4 as shown in FIG. In step S5, the difference detection unit 14
Based on the part information, the analysis result information 500 and the diagnosis support information 502 are determined as the first corresponding findings, and the analysis result information 501 and the diagnosis support information 503 are determined as the second corresponding findings.
It is assumed that the difference detection result information 504 of the first corresponding finding and the difference detection result information 505 of the second corresponding finding are obtained.

  The term importance dictionary 150 that constitutes the medical importance calculator 15 that performs the process of step S7 has, as a database, importance rank information 600 as shown in FIG. 8, for example. Since the difference detection result information 504 shown in FIG. 7 is difference detection result information between the interpretation report analysis result information 500 and the diagnosis support information 502, this difference detection result information relates to “lung cancer” with respect to “lesion”. . The medical importance calculation unit 15 determines that the importance rank of “lung cancer” is “7” by collating with the importance rank information 600, and sets the importance rank of the difference detection result information 504 of FIG. 7 ”. On the other hand, since the difference detection result information 505 in FIG. 7 is difference detection result information between the interpretation report analysis result information 501 and the diagnosis support information 503, this difference detection result information is related to “pneumonia” with respect to “lesion”. . Therefore, the medical importance calculation unit 15 determines that the importance rank of “pneumonia” is “1” by collating with the importance rank information 600, and the importance rank of the difference detection result information 505 in FIG. Is set to “1”.

(Step S8)
Next, the difference presentation unit 16 presents the difference information detected in step S5 on the result of interpretation by the doctor input in step S1, with the expression changed according to the medical importance calculated in step S7. . At this time, for example, the difference presenting unit 16 detects the difference detected in step S5 on the interpretation result by the doctor input in step S1 only when the medical importance calculated in step S7 is larger than a preset threshold. It may be configured to perform a process of displaying information. This process will be specifically described with reference to FIGS.

  First, consider processing based on the medical importance calculated in step S7. As described in the description of step S7, the importance rank of the difference detection result information 504 in FIG. 7 is calculated as 7, and the importance rank of the difference detection result information 505 is calculated as 1. In this case, for example, when the threshold value of the medical importance rank is set to 5, the difference presentation unit 16 sets only the difference in findings related to lung cancer having a medical importance rank exceeding 5 as the presentation content 700 in FIG. As shown in FIG. 4, the interpretation result input in step S1 is displayed together with the display. For example, when the medical importance rank threshold is set to 0, the difference presentation unit 16 displays all the difference information of the interpretation result input in step S1 as shown in the presentation content 701 of FIG. Display with display.

  As explained above, according to the configuration of the first embodiment, medically important differences between the interpretation report entered by the doctor and the diagnosis support information calculated by the computer can be presented on the interpretation report. It becomes possible. Therefore, the medically important difference information can be presented without bothering the doctor by presenting the difference information that is not medically important.

[Second Embodiment]
In the first embodiment, as a specific process of the medical importance calculation unit 15, the process of defining the medical importance by the content of the detected difference information has been described as an example. However, the process performed by the medical importance calculation unit 15 of the present invention is not limited to this. Here, some of other embodiments of the medical importance calculation unit 15 in the present invention will be described.

<Calculation of medical importance by affiliation class>
The medical importance calculation unit 15 may define the difference result information detected by the difference detection unit 14 according to the class to which the difference information belongs. For example, the class to which the word appearing in the difference result information belongs is classified into one of “part”, “part supplement”, “symptom”, “symptom supplement”, “disease name”, and “examination / treatment”. The medical importance is increased for the differences related to “part”, “symptom”, and “disease name”, and the medical importance is assigned to the difference related to “part supplement”, “symptom supplement”, and “examination / treatment”. Make it smaller. Thereby, with respect to the difference information detected by the difference detection unit 14, the medical importance can be calculated according to the class of the word to which the difference information belongs.

<Calculation of medical importance based on the size of the content difference>
Further, the medical importance calculation unit 15 may calculate the medical importance according to the magnitude of the difference detected by the difference detection unit 14. For example, when a difference in lung nodule size is detected as a difference belonging to the “symptom supplement” class, the medical importance can be calculated according to the difference in numerical information indicating the size. At this time, for example, a numerical difference between “1 mm” and “2 mm” may be set to “difference: 1 mm” as an absolute value difference. In addition, “difference: double” can be calculated as a ratio of magnitudes between numerical values, and the medical importance corresponding to the difference can be calculated.

  In addition to the difference in numerical information, medical importance can be calculated according to the magnitude of the difference in the meaning of text information such as words. In this case, for example, “pulmonary emphysema” and “chronic bronchitis” are both types of obstructive pulmonary disease, so the medical importance of the difference is calculated to be small, while “emphysema” and “lung cancer” Since these are different types of lesions, the medical importance of the difference can be calculated greatly. Thereby, the medical importance according to the magnitude of the difference in medical meaning can be calculated. Note that the magnitude of such “difference” between disease names is registered in advance as a table.

<Calculation of medical importance by combining difference contents>
Further, the medical importance level calculation unit 15 may calculate the medical importance level according to the combination of the contents of the differences detected by the difference detection unit 14. For example, when a serious lesion name is written as diagnosis support information in spite of the fact that the name of the disease whose effect on the life of the examinee is slight was written on the interpretation report completed by the doctor Medical importance can be increased. In addition, although there is a difference between the interpretation entered by the interpretation doctor and the diagnosis support information generated by the computer, the medical importance can be lowered if both have minor lesion names written.

<Calculation of medical importance based on the presence or absence of corresponding findings>
Further, the medical importance calculation unit 15 calculates the medical importance from the detection result by the difference detection unit 14 depending on whether or not the interpretation result corresponding to the diagnosis support information exists on the interpretation report. May be. For example, when there is no interpretation result corresponding to the diagnosis support information, a predetermined importance is assigned to the diagnosis support information. Alternatively, when the interpretation result does not exist according to the class (item), the importance is set in advance, and when there is no interpretation result corresponding to the diagnosis support information, the importance depends on the class (item) to which the word belongs. The set importance may be given. In this case, for example, a medical importance can be calculated high for diagnosis support information that cannot be matched with an interpretation report, and an oversight by a doctor can be prevented.

<Others>
Moreover, you may comprise the medical importance calculation part 15 so that it may calculate with the method which combined the various calculation methods regarding calculation of the above-mentioned medical importance. For example, as a result of the difference detection, both the medical importance calculated by the class to which the word of the difference part belongs and another medical importance calculated by the magnitude of the difference between the contents described in the difference part It is possible to calculate the medical importance taking into account.

[Third Embodiment]
In 1st Embodiment, the process which switches the presence or absence of presentation of difference information as an example as a specific process of the difference presentation part 16 was demonstrated as an example. However, the process of the difference presentation part 16 of this invention is not limited to this. Here, another embodiment of the difference presentation unit 16 will be described.

<Type of expression>
The difference presentation unit 16 displays the difference information detected by the difference detection unit 14 on the interpretation report input by the interpretation report input unit 10 according to the medical importance calculated by the medical importance calculation unit 15. The display mode may be switched and presented. For example, depending on the medical importance, the character display mode such as the character size, the type of character, the character color, the blinking state of the character, the use of a pop-up display, and the like can be switched and presented. Further, the display mode to be changed is not limited to the display mode of the character itself, and other display modes such as the background color of the character and the annotation display for prompting pop-up can be used. Thus, the user can recognize the importance of the difference information based on the difference in characters and other display modes.

<With no difference>
Further, the difference presenting unit 16 also determines that “no difference” or a character having the same meaning is used even when the difference is not presented based on the processing results of the difference detecting unit 14 and the medical importance calculating unit 15. You may comprise so that a symbol etc. may be shown. Thus, even when the difference is not presented, the user can distinguish whether there is no difference as a result of the difference detection process or whether the system itself is not operating normally.

[Other Embodiments]
Although the embodiment has been described in detail above, the present invention can take an embodiment as a system, apparatus, method, program, storage medium, or the like. Specifically, the present invention may be applied to a system composed of a plurality of devices, or may be applied to an apparatus composed of a single device.

  In the present invention, the functions of the above-described embodiments are achieved by supplying a software program directly or remotely to a system or apparatus, and the computer of the system or apparatus reads and executes the supplied program code. Including the case. In this case, the supplied program is a computer program corresponding to the flowchart shown in the drawings in the embodiment.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. In other words, the present invention includes a computer program itself for realizing the functional processing of the present invention.

  In that case, as long as it has the function of a program, it may be in the form of object code, a program executed by an interpreter, script data supplied to the OS, or the like.

  Examples of the computer-readable storage medium for supplying the computer program include the following. For example, floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card, ROM, DVD (DVD-ROM, DVD- R).

  As another program supply method, a client computer browser is used to connect to a homepage on the Internet, and the computer program of the present invention is downloaded from the homepage to a recording medium such as a hard disk. In this case, the downloaded program may be a compressed file including an automatic installation function. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the present invention.

  Further, the program of the present invention may be encrypted, stored in a storage medium such as a CD-ROM, and distributed to users. In this case, a user who has cleared a predetermined condition is allowed to download key information for decryption from a homepage via the Internet, execute an encrypted program using the key information, and install the program on the computer. You can also.

  In addition to the functions of the above-described embodiment being realized by the computer executing the read program, the embodiment of the embodiment is implemented in cooperation with an OS or the like running on the computer based on an instruction of the program. A function may be realized. In this case, the OS or the like performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

  Furthermore, the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, so that part or all of the functions of the above-described embodiments are realized. May be. In this case, after a program is written in the function expansion board or function expansion unit, the CPU or the like provided in the function expansion board or function expansion unit performs part or all of the actual processing based on the instructions of the program.

Claims (18)

Detecting means for detecting a difference between first medical information acquired from information created by a user and second medical information obtained by computer processing for medical information;
Control means for displaying the difference on a display unit in a display form according to a combination of a lesion name included in the first medical information and a lesion name included in the second medical information;
A diagnostic support apparatus comprising: A decision means for determining importance according to a combination of a lesion name included in the first medical information and a lesion name included in the second medical information;
The diagnosis support apparatus according to claim 1, wherein the control unit displays the difference on the display unit in a display form according to the importance determined by the determination unit.   The control means displays the difference on the display unit when the importance is greater than or equal to a predetermined threshold, and does not display the difference on the display unit when the importance is less than a predetermined threshold. The diagnosis support apparatus according to claim 2. The diagnosis support apparatus according to claim 2, wherein the control unit displays the difference on the display unit in a character display mode according to the importance determined by the determination unit. The diagnosis support apparatus according to claim 4, wherein the display mode of the character is at least one of a character size, a font, a character color, a character background color, and a pop-up display. A table further associating the combination of the lesion name and the importance,
The diagnosis support apparatus according to claim 2, wherein the determination unit determines the importance using the table.   The determination means increases the importance when the lesion name included in the first medical information has a smaller effect on the life than the lesion name included in the second medical information. 6. The diagnosis support apparatus according to claim 2, wherein the diagnosis support apparatus is characterized in that   The diagnosis support apparatus according to claim 1, wherein the medical information is an image. A detection step of detecting a difference between the first medical information acquired from the information created by the user and the second medical information obtained by computer processing on the medical information;
A control step of causing the display unit to display the difference in a display form according to a combination of a lesion name included in the first medical information and a lesion name included in the second medical information;
A control method comprising:   The computer program for functioning a computer as each means of the diagnostic assistance apparatus as described in any one of Claims 1 thru | or 8.   A computer-readable storage medium storing the computer program according to claim 10. Detecting means for detecting a difference between first medical information acquired from information created by a user and second medical information obtained by computer processing for medical information;
Control means for displaying the difference on the display unit in a display form according to the lesion name included in the first medical information and the lesion name included in the second medical information;
A diagnostic support apparatus comprising: A detection step of detecting a difference between the first medical information acquired from the information created by the user and the second medical information obtained by computer processing on the medical information;
A control step of causing the display unit to display the difference in a display form according to a lesion name included in the first medical information and a lesion name included in the second medical information;
A control method comprising:   A computer program for causing a computer to function as each means of the diagnosis support apparatus according to claim 12.   A computer-readable storage medium storing the computer program according to claim 14. Detecting means for detecting a difference in lesion size between the first medical information acquired from the information created by the user and the second medical information obtained by computer processing on the medical information;
Control means for displaying the difference on a display unit in a display form according to the magnitude of the difference;
A diagnostic support apparatus comprising:   A computer program for causing a computer to function as each means of the diagnosis support apparatus according to claim 16.   A computer-readable storage medium storing the computer program according to claim 17.

Images