JP7504600B2 - Analysis Equipment - Google Patents

Description

An embodiment of the present invention relates to an analysis device.

In recent years, Autopsy Imaging (AI) has been adopted as a method for determining the cause of death of deceased people. AI uses postmortem images taken with X-ray CT (Computed Tomography) devices or MRI (Magnetic Resonance Imaging) to diagnose abnormalities such as lesions and wounds that occurred during the person's life and determine the cause of death.

In recent years, X-ray CT scanners and MRI scanners are capable of high-speed imaging, so in order to determine the cause of death more accurately, it is recommended that AI images the entire body using X-ray CT scanners or MRI scanners. The time required for imaging in this case usually ranges from a few minutes to a dozen minutes. However, the number of image slices of the entire body captured is enormous, amounting to thousands of slices, making it extremely difficult for radiologists to determine the cause of death from these images. In addition, it takes time to display these huge numbers of images on a monitor, etc.

Recently, CAD (Computer-aided Detection/Diagnosis) has been put to practical use, which detects abnormal shadows from X-ray CT and MRI images and assists doctors in making diagnoses. CAD is usually used on living people, and in order to diagnose diseases in specific parts of the body, such as the head, chest, or abdomen, it detects abnormal shadows from captured images using an algorithm appropriate for that part.

In the aforementioned AI, imaging of the entire body of a corpse is recommended to determine the cause of death, and the number of slice images is enormous, making it difficult for radiologists to determine the cause of death by looking at all of these slice images. In addition, because corpses have characteristics that differ from those of living bodies, radiologists who are not accustomed to interpreting corpse images may make an incorrect determination of the cause of death.

For this reason, images that are difficult to interpret to determine the cause of death will be sent to institutions that specialize in interpreting postmortem images, such as the AI Information Center. However, in the coming society of high death rates, there is a risk that specialized institutions will not be able to function properly due to a lack of manpower. Furthermore, if the postmortem images are not taken in the first place in the conditions necessary for interpretation, even specialized institutions may have difficulty determining the cause of death from the images.

International Publication No. 2014/188937 JP 2015-136431 A Patent No. 5725797

The purpose of this embodiment is to provide an analysis device that makes it easier to determine the cause of death of a subject.

The analysis device according to this embodiment includes a plurality of different analysis processing units that obtain a first analysis result related to the cause of death based on information about the subject, and an integrated processing unit that obtains a second analysis result related to the cause of death based on the plurality of first analysis results.

FIG. 1 is a block diagram showing an overall configuration of an analysis system according to an embodiment. 2 is a flowchart illustrating an analysis process executed by an analysis device in the analysis system shown in FIG. 1 . FIG. 13 is a diagram showing an example of a table by part for explaining a specific example of integration processing executed by the integration processing function. FIG. 13 shows an example of a cause of death determination table used by the integration processing function to perform further analysis based on the first analysis result, determine possible causes of death, and generate a second analysis result.

Below, an analysis device according to this embodiment and an analysis system including the analysis device will be described with reference to the drawings. In the following description, components having substantially the same functions and configurations will be given the same reference numerals, and duplicated descriptions will be provided only when necessary.

In the analysis device according to this embodiment, multiple different types of analysis processing units derive first analysis results relating to the cause of death based on the subject's information, and then the integrated processing unit derives second analysis results that are candidates for the cause of death using the reliability of the first analysis results and the presence or absence of inconsistencies. The details are explained below.

Figure 1 is a block diagram explaining the overall configuration of an analysis system 1 according to this embodiment. The analysis system 1 shown in this Figure 1 is a system installed in, for example, a hospital. As shown in this Figure 1, the analysis system 1 according to this embodiment is configured to include an analysis device 2, an image capturing device 10, an external information storage device 12, and a network NT that connects these devices so that they can communicate with each other.

The imaging device 10 is a device for capturing images of a subject, and is, for example, composed of an X-ray CT device, an MRI device, or the like. In this embodiment, in particular, the imaging device 10 captures X-ray images of different parts of a subject, which is a corpse. For example, the imaging device 10 captures images of the subject's head, neck, chest, abdomen, and limbs, and generates X-ray images of each part.

The external information storage device 12 stores external information about the subject, which is a corpse. For example, in this embodiment, external information including at least one of the following is stored in association with the subject: whether or not cardiopulmonary resuscitation was performed, time since death, weather information, and symptoms reported during life.

In this embodiment, the analysis device 2 is configured to include a control circuit 20, a program storage circuit 22, a display unit 24, an input unit 26, a communication unit 28, and an information storage circuit 30. These components are connected to each other via an internal bus or the like so that they can cooperate with each other.

The control circuit 20 is a calculation device that performs overall control of the analysis device 2 and also performs various other calculation processes and control processes. The control circuit 20 is, for example, composed of a processor. Here, the term processor refers to circuits such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)).

The processor realizes various functions by reading and executing the programs stored in the program storage circuitry 22. Note that instead of storing the programs in the program storage circuitry 22, the processor may be configured to directly incorporate the programs into its circuitry. In this case, the processor realizes its functions by reading and executing the programs incorporated into the circuitry. Note that the processor is not limited to being configured as a single processor circuit, and may be configured as a single processor by combining multiple independent circuits to realize its functions. Furthermore, the multiple components in FIG. 1 may be integrated into a single processor to realize its functions.

As will be described in more detail later, the control circuit 20 according to this embodiment reads and executes a program from the program storage circuit 22 to realize an image acquisition function 20a, an image addition determination function 20b, an analysis processing function 20c, an integration processing function 20d, a first output function 20e, a second output function 20f, and a standard corpse construction function 20g.

The program memory circuit 22 is a circuit that stores and holds various programs executed by the control circuit 20, etc. This program memory circuit 22 is realized, for example, by a semiconductor memory element such as a RAM (Random Access Memory), a ROM (Read Only Memory), or a flash memory, a hard disk, an optical disk, etc.

The display unit 24 displays various information. For example, the display unit 24 displays and outputs images of the subject captured by the image capturing device 10, output results of the control circuit 20, etc. It can also configure a GUI (Graphical User Interface) for accepting various operations from the operator. For example, the display unit 24 is configured with a liquid crystal display, a CRT (Cathode Ray Tube) display, etc.

The input unit 26 accepts various input operations from the operator, converts the accepted input operations into electrical signals, and outputs the electrical signals to the control circuit 20. For example, the input unit 26 accepts from the operator the start and end of imaging of a subject, which is a corpse, using the imaging device 10, and the conditions for imaging the subject by body part using the imaging device 10. For example, the input unit 26 is realized by a mouse, keyboard, trackball, switch, button, joystick, etc.

The communication unit 28 is connected to the network NT within the hospital and controls communication between the analysis device 2, the image capture device 10, and the external information storage device 12. That is, via the communication unit 28, the analysis device 2 is connected to the image capture device 10 and the external information storage device 12 so as to be able to exchange information.

The information storage circuit 30 is a circuit that stores various information in the analysis device 2 as data. This information storage circuit 30 is realized, for example, by a semiconductor memory element such as a random access memory (RAM) or a flash memory, a hard disk, an optical disk, etc. As will be described in detail later, in this embodiment, the information storage circuit 30 comprises a time-of-death chart storage circuit 30a, a region-specific image storage circuit 30b, and an analysis result storage circuit 30c.

Next, referring to FIG. 2, the process contents when the analysis device 2 executes an analysis process on a subject that is a corpse will be described. FIG. 2 shows a flowchart explaining the analysis process executed by the analysis device 2 in this embodiment. This analysis process is realized by the control circuit 20 reading and executing the analysis process program stored in the program storage circuit 22.

The analysis scenario of the subject is as follows: That is, the analysis process according to this embodiment will be described by taking the following subject as an example.
A man was found dead in his living room at home. He was 78 years old.
- The body was found in a prone position. - It was winter, and according to the weather report, the maximum temperature had been a low 7°C for the past week (the heating in the living room of the home was not being used).
-Found wearing the clothes he would wear when going out (wearing a coat).
- No visible injuries on the body surface.
-Based on the testimony of the family who discovered the body, it appears that about a day had passed since the death.
-The ambulance team performed cardiopulmonary resuscitation, including chest compressions.
- According to the patient's medical records, he is currently receiving treatment for sleep apnea and high blood pressure.

Let's say a body like the one above (hereafter referred to as Subject A) was discovered at home. A medical examiner was called to the home after being notified by a family member living nearby. Upon inspection of the body's exterior, no noticeable abnormalities were found, and it was determined that there was no foul play involved. Furthermore, interviews with the family revealed that the patient had been receiving treatment for sleep apnea syndrome and high blood pressure, and it was presumed that the patient had died of internal causes due to a cardiovascular disease such as a stroke or acute myocardial infarction. As the family did not wish for an autopsy, they decided to request a post-mortem CT scan (autopsy imaging) from an affiliated hospital in order to determine the exact cause of death.

Using this scenario, the procedure for determining the cause of death at a hospital will be explained. First, the doctor in charge at the hospital who receives a request for autopsy imaging will obtain subject A's medical record based on the patient's doctor's appointment card brought by the family, check the patient's medical history and test results before death (vital data and diagnostic images), and enter only the information that is useful for determining the cause of death, or all of the information, into subject A's medical record at the time of death. If there is a lifetime medical record of subject A that records health information from the time of fetal birth to the present, it is also possible to add the information to this.

In addition, the time since subject A's death, based on the testimony of family members and the medical examiner's judgment, the temperature and humidity of the environment where subject A died, including whether or not air conditioning was used, subject A's clothing at the time of discovery, and the results of external observation are also input. This input information on the death chart is stored in the death chart storage circuit 30a in the information storage circuit 30.

In addition, weather information from the estimated time of death to the present may also be entered into the death chart. In this embodiment, the weather information is stored, for example, in the external information storage device 12, and may be automatically acquired by the analysis device 2 based on the estimated time of death, or may be input into the analysis device 2 by the doctor in charge, who is the operator. In this embodiment, this additional information is also stored and memorized in the death chart storage circuit 30a in the information storage circuit 30 as information related to the death chart.

In parallel with these tasks, the operator, such as the attending doctor or the attending radiologist, also prepares for a postmortem CT scan to capture images of individual parts of subject A. That is, the operator, such as the attending doctor or the attending radiologist, takes steps such as placing subject A's body in a body bag to prevent contamination of the imaging device 10, and then sends subject A into the imaging device 10 (step S1). For example, if the imaging device 10 is an X-ray CT device, the subject is sent into the gantry of the X-ray CT device.

Next, the radiological technologist starts imaging using the imaging device 10 for each part, such as the head, neck, chest, abdomen, and extremities, according to the imaging range, imaging position, and imaging conditions for autopsy imaging shown in, for example, the "Ai Examination Guidelines" http://www.jart.jp/news/tclj8k0000000we0-att/Aiguideline_170310.pdf. The imaging conditions for each part may be set automatically when, for example, the "Automatic Autopsy Imaging Imaging Button" of the imaging device 10 to which the above conditions have been input is selected, or the operator, who is the doctor in charge or the radiological technologist in charge, may manually input the imaging conditions into the analysis device 2 or the imaging device 10 while taking into account the condition of the subject A (step S2). In addition, since the subject is generally a corpse, the dose of X-rays irradiated to the subject when identifying the cause of death of the corpse can be set to be greater than the dose of X-rays irradiated to the subject when diagnosing the patient. Once the operator, who may be a doctor or a radiological technologist in charge, has completed setting the imaging conditions for each part, he or she inputs an instruction to start the examination to the analysis device 2 via the input unit 26 (step S3).

When the examination begins, the image acquisition function 20a of the control circuit 20 switches the database in which the captured images are saved when the imaging conditions are switched, i.e., when the part of the subject to be imaged changes (step S4). In this embodiment, the image acquisition function 20a of the control circuit 20 stores and memorizes the captured images in the part-specific image storage circuit 30b of the information storage circuit 30, so that the database that stores the captured images for each part of the subject is formed in the part-specific image storage circuit 30b of the information storage circuit 30.

Specifically, under the control of the image acquisition function 20a of the control circuit 20, the captured image data of the head is stored in a head database 30b1, the captured image data of the neck is stored in a neck database 30b2, the captured image data of the chest is stored in a chest database 30b3, the captured image data of the abdomen is stored in an abdomen database 30b4, and the captured image data of the extremities is stored in an extremity database 30b5. In this way, in this embodiment, the captured images are stored by body part of the subject, and databases 30b1 to 30b5 are formed.

The image addition determination function 20b of the control circuit 20 determines whether the X-ray dose, imaging range, etc. of the data related to the captured images stored in these databases 30b1 to 30b5 are appropriate for images for a postmortem CT examination (step S5). If there is a problem such as an insufficient dose or a missing required image, the image addition determination function 20b causes the image acquisition function 20a to capture additional images of the missing images (S6') or outputs a warning. For example, the image addition determination function 20b notifies the operator by displaying a warning on the display unit 24.

The image addition determination function 20b of the control circuit 20 may check with the database control circuit 30b6 whether the images necessary to investigate the cause of death of the subject are available, rather than being performed by the image addition determination function 20b. In this case, the image addition determination function 20b queries the database control circuit 30b6 in the information storage circuit 30 before the imaging of the subject is completed, and confirms whether the images necessary for the analysis processing function 20c to perform the analysis are available (step S5). That is, the image addition determination function 20b determines whether the images necessary for the analysis processing function 20c to perform the analysis have been captured by the imaging device 10 while the subject is in the imaging device 10 that captures the image of the subject. Then, if the image addition determination function 20b determines that there are insufficient images, it causes the image acquisition function 20a to additionally capture the missing images (S6'). Alternatively, if the image addition determination function 20b of the control circuit 20 determines that there are insufficient images, it outputs an instruction to add images to, for example, the display unit 24 to warn the operator.

When the information necessary for determining the cause of death is collected, the image acquisition function 20a of the control circuit 20 notifies an operator, such as a doctor or a clinical radiologist, that imaging has ended, removes the body of subject A from the imaging device 10, and ends the image acquisition process of the subject (step S6). If the imaging device 10 is an X-ray CT device, the doctor or clinical radiologist removes the subject from the gantry of the X-ray CT device, and ends the image acquisition process.

Next, the analysis processing function 20c performs analysis of the images of the subject acquired by the image acquisition function 20a of the control circuit 20 for each part of the body. That is, the analysis processing function 20c first imports the autopsy information stored in the death chart for subject A and external information such as temperature history (step S7). Specifically, the analysis processing function 20c acquires information related to the death chart from the death chart storage circuit 30a, and imports the autopsy information and external information from the death chart. The analysis processing function 20c can also import external information directly from the external information storage device 12.

In the analysis processing function 20c according to this embodiment, an analysis function for analyzing images for each part of the subject is provided. That is, the analysis processing function 20c includes a head analysis function 20c1 for analyzing the image of the subject's head stored in the head database 30b1, a neck analysis function 20c2 for analyzing the image of the subject's neck stored in the neck database 30b2, a chest analysis function 20c3 for analyzing the image of the subject's chest stored in the chest database 30b3, an abdominal analysis function 20c4 for analyzing the image of the subject's abdomen stored in the abdominal database 30b4, and a limb analysis function 20c5 for analyzing the image of the subject's limbs stored in the limb database 30b5.

Each of the analysis functions 20c1 to 20c5 reads the resuscitation information or the time since death information, and analyzes the image using an abnormal shadow detection algorithm for the relevant part (step S8). Specific abnormal shadow detection algorithms are known, for example, as disclosed in Patent No. 5725797 (medical image processing device for image interpretation). However, in this embodiment, in addition to the resuscitation information or the time since death information, external surface information, medical history and genetic information from medical record information, verbal information from interviews, temperature history information obtained from the external information storage device 12, etc. may also be taken into account when interpreting the image.

In the abnormal shadow detection algorithm disclosed in Patent No. 5725797, the head analysis function 20c1, neck analysis function 20c2, chest analysis function 20c3, abdominal analysis function 20c4, and limb analysis function 20c5 each obtain an analysis result based on the image of each part, and output the result to complete the analysis process.

However, in the analysis device 2 according to this embodiment, the integration processing function 20d uses the analysis result obtained by the analysis processing function 20c as the first analysis result, and obtains and presents the most likely cause of death as the second analysis result (step S9). For example, the integration processing function 20d comprehensively judges the first analysis result based on the reliability of the first analysis result obtained by the analysis functions 20c1 to 20c5 to obtain the second analysis result. Also, instead of or in addition to the reliability of the first analysis result, the presence or absence of mutual contradictions in the first analysis results obtained by the analysis functions 20c1 to 20c5 is used to obtain the second analysis result. Here, the strength of validity of the second analysis result may be expressed as a degree of agreement. This degree of agreement is a value calculated by the integration processing function 20d that indicates the strength of validity of the second analysis result.

Figure 3 is a diagram showing an example of a body part table to explain a specific example of the analysis processing executed by the analysis processing function 20c and the integration processing executed by the integration processing function 20d. Figure 4 is a diagram showing an example of a cause of death determination table used in which the analysis processing function 20c performs image analysis by body part to obtain a first analysis result, and the integration processing function 20d performs further analysis based on the first analysis result to determine candidates for the cause of death. As shown in Figure 4, the cause of death determination table in this embodiment is provided with "image findings," "serial number," "external findings," "possible cause of death/important items," "cause of death relevance," "evidence strength (reliability)," and "remarks" by body part, and information for identifying the cause of death is stored.

First, as shown in FIG. 3, for example, based on an image of the subject's head acquired from the head database 30b1, the head analysis function 20c1 detects the presence of a large number of punctate low-attenuation areas, and determines lacunar infarction (asymptomatic cerebral infarction) as the first analysis result based on these large number of punctate low-attenuation areas. In the case of lacunar infarction (asymptomatic cerebral infarction), acute cerebral infarction is predicted as the "probable cause of death/important item", but since it can be determined from the cause of death determination table in FIG. 4 that lacunar infarction based on a large number of punctate low-attenuation areas is usually unlikely to be a cause of death, the head analysis function 20c1 determines that the cause of death association level is 3 out of 5 levels. This number may be registered in advance as the cause of death association level of lacunar infarction in the cause of death determination table in FIG. 4, or the head analysis function 20c1 may calculate and determine it together with other information (step S8-1).

In a similar manner, the neck analysis function 20c2 analyzes the image of the subject's neck obtained from the neck database 30b2. However, the neck analysis function 20c2 does not detect any abnormalities in the image and determines that there are no abnormalities in the neck (step S8-2).

Next, the chest analysis function 20c3 analyzes the chest image of the specimen obtained from the chest database 30b3. From this chest image, the chest analysis function 20c3 detects multiple consecutive fractures symmetrically arranged on the left and right sides of the anterior chest. However, the chest analysis function 20c3 refers to the medical record at the time of death and determines that this is "due to cardiopulmonary resuscitation." The chest analysis function 20c3 also detects a ground-glass opacity that forms a horizontal plane on both lungs in the chest image. However, the chest analysis function 20c3 determines that this ground-glass opacity is "postmortem change (hemostasis)." The chest analysis function 20c3 determines the degree of association with the cause of death to be 0 for both.

Furthermore, the chest analysis function 20c3 detects the presence of a high-intensity shadow in the coronary artery in the chest image. Since this is calcification of the coronary artery, the chest analysis function 20c3 determines that the "probable cause of death/important item" is "acute myocardial infarction". Furthermore, since "acute myocardial infarction" based on the high-intensity shadow in the coronary artery in the cause of death determination table of FIG. 4 has a cause of death relevance degree of 5, the chest analysis function 20c3 determines that the cause of death relevance degree based on this high-intensity shadow in the coronary artery is 5. Furthermore, the chest analysis function 20c3 detects a high-absorption mold-like structure in the great cardiac vessels from the chest image. The chest analysis function 20c3 determines that this high-absorption mold-like structure in the great cardiac vessels is a postmortem change/pork fat-like clot in the great cardiac vessels. When lard-like blood clots are found in the great cardiac vessels, it is generally considered that the death is not sudden, so the chest analysis function 20c3 determines that the "probable cause of death/important item" is "not sudden death" (step S8-3).

The abdominal analysis function 20c4 analyzes the abdominal image acquired from the abdominal database 30b4. The abdominal analysis function 20c4 detects a large amount of low absorption area (gas) in the hepatic blood vessels in the abdomen from the abdominal image and judges this to be a postmortem change (decay). The abdominal analysis function 20c4 also detects a linear low absorption area in the liver parenchyma from the abdominal image, but judges this to be a liver rupture and "simple deep injury". However, since the imaging in the imaging device 10 such as an X-ray CT device is non-contrast imaging and the image is not clear, the abdominal analysis function 20c4 sets the "possible cause of death/important item" to "suspected simple deep injury". In addition, since the simple deep injury based on the linear low absorption area of the liver parenchyma in the cause of death determination table in FIG. 4 has a cause of death relevance degree of 4, the abdominal analysis function 20c4 judges the cause of death relevance degree of this linear low absorption area of the liver parenchyma to be 4 (step S8-4).

The limb analysis function 20c5 analyzes the images of the limbs obtained from the limb database 30b5. Here, the limb database 30b5 does not detect any abnormalities in the images of the limbs, and determines that there are no abnormalities in the limbs (step S8-5).

After the analysis process by the head analysis function 20c1, neck analysis function 20c2, chest analysis function 20c3, abdominal analysis function 20c4, and limb analysis function 20c5 described above is completed, the integration processing function 20d starts a discussion based on the first analysis results output by the head analysis function 20c1, neck analysis function 20c2, chest analysis function 20c3, abdominal analysis function 20c4, and limb analysis function 20c5, and outputs a second analysis result regarding the cause of death (step S9).

For example, when the head analysis function 20c1 refers to the cause of death determination table in FIG. 4, it can be seen that when "multiple punctate low absorption areas" are detected as image findings in a head image, acute cerebral infarction is listed as a "possible cause of death/important item". It can also be seen that the cause of death relevance is 3 out of 5, and the evidence strength (reliability) is 30. Here, the cause of death relevance, which is evaluated on a 5-point scale, indicates that the higher the value, the more likely it is to be a cause of death. Furthermore, the evidence strength (reliability) indicates whether the image finding is likely to be a "possible cause of death/important item" or not, and is evaluated with a value from 0 to 100. In this embodiment, for example, the higher the value of the evidence strength (reliability), the more likely it is to be a "possible cause of death/important item".

Furthermore, for example, by referring to the cause of death determination table in FIG. 4, the chest analysis function 20c3 can determine that, for example, when a "high intensity shadow in a coronary artery" is detected as an image finding in a chest image, acute myocardial infarction is listed as a "possible cause of death/important item." It can also be determined that the cause of death relevance is 5 out of 5, and the evidence strength (reliability) is 50. In this way, using the first analysis results in the analysis functions 20c1 to 20c5 and the cause of death determination table in FIG. 4, the integration processing function 20d consults on the first analysis results derived from multiple different analysis processes, and derives a second analysis result that is a candidate cause of death.

For example, in the example of FIG. 3, the head analysis function 20c1 presents a cause of death of acute cerebral infarction, but the evidence strength that lacunar infarction is the cause of acute cerebral infarction is 30, whereas the evidence strength of the judgment of "not sudden death" presented by the chest analysis function 20c3 is 90, so the integrated processing function 20d rejects the judgment that death was due to acute cerebral infarction. The degree of agreement, which indicates the strength of validity of the second analysis result of "rejecting the judgment that death was due to acute cerebral infarction", which is the result of discussion between the analysis functions, is shown as, for example, 80%. This degree of agreement is calculated, for example, from the relationship between the cause of death relevance of other items and the evidence strength. The integrated processing function 20d also rejects the cause of death of "acute myocardial infarction" presented by the chest analysis function 20c3 itself. The abdominal analysis function 20c4 judges that the large amount of low absorption areas (gas) in the liver blood vessels is a postmortem change due to decomposition, and therefore the degree of association with the cause of death is zero. Based on the information based on the medical record at the time of death, which states that it was one day after death and the temperature was low, the integration processing function 20d judges that decomposition would not have progressed that far, and rejects the analysis result that it is a postmortem change. However, since the judgment that it is a postmortem change presented by the abdominal analysis function 20c4 cannot be completely denied, the approval degree, which indicates the strength of validity of the second analysis result, which is the result of the discussion by the integration processing function 20d, is set to the intermediate value of 50%.

As a result, the abdominal analysis function 20c4 presents "suspected simple deep damage to the liver" as a possible cause of death, but the integration processing function 20d places the decision "on hold" because this contradicts the external findings of "minor bruises on the body surface."

Next, the series of judgments made by the integrated processing function 20d are presented to the attending physician as the second analysis result, which is the result of assistance in determining the cause of death (step S10). In this embodiment, the first output function 20e of the control circuit 20 outputs and displays the second analysis result, which is the judgment result of the integrated processing function 20d, on, for example, the display unit 24. Note that the output destination of the first output function 20e is not limited to the display unit 24, but is arbitrary. For example, the first output function 20e may output the second analysis result to a printing means such as a printer.

Based on the second analysis result output by the first output function 20e, the attending physician can determine that a detailed examination of the liver is necessary, and an X-ray CT scan of the abdomen is performed using a contrast agent. Specific methods for imaging a corpse are known, for example, as disclosed in Patent No. 5575515 (Medical Image Diagnostic System and Contrast Fluid Delivery Apparatus), and various methods exist, such as using an embalming device.

When "simple deep liver damage" is confirmed by abdominal X-ray CT imaging using a contrast agent, this is a relatively high judgement of cause of death relevance level 4, and the attending physician will determine this as the cause of death. The inconsistency of the minor bruises on the body surface compared to the liver damage can be presumed to be due to the fact that subject A's body surface was covered by a thick coat or the like. The final cause of death is determined by a comprehensive judgment made by the attending physician, medical examiner, police officer, etc., but this may also be determined by the integrated processing function 20d performing analysis processing based on previously stored information.

In addition, although the doctor in charge here decided to perform imaging using an X-ray CT scanner with a contrast agent, the integrated processing function 20d may decide and perform the imaging automatically. In this case, the body may be kept waiting, with the doctor's knowledge, inside the imaging device 10, for example, inside the gantry of the X-ray CT scanner, until the cause of death is determined.

In addition, here, the analysis processing function 20c and the integration processing function 20d are set to perform image interpretation support to identify the cause of death of the subject until the end, but if the analysis processing of the analysis processing function 20c and the integration processing function 20d cannot identify the cause of death, it becomes a difficult image interpretation case, and a request is made to a specialized institution such as an Ai information center to identify the cause of death (step S11). In this embodiment, the integration processing function 20d generates undetermined information indicating that the cause of death cannot be identified, and the second output function 20f of the control circuit 20 outputs the undetermined information to the display unit 24 for display. Note that the output destination of the second output function 20f is not limited to the display unit 24 and is arbitrary. For example, the second output function 20f may be set to output the undetermined information to a printing means such as a printer.

In this way, the hospital's doctor or radiologist can determine the cause of death of the subject based on the second analysis results, which are information generated by the integrated processing function 20d to assist in identifying the cause of death of the subject, so even doctors or radiologists who do not necessarily have much knowledge or experience in identifying the cause of death can make a proper identification of the cause of death. As a result, only in cases where it is difficult for a general hospital to identify the cause of death, requests are made to specialized institutions to identify the cause of death, reducing the burden on the specialized institutions. This makes it possible to prevent with a high degree of certainty that specialized institutions that identify the cause of death based on the remains will become dysfunctional due to a lack of manpower.

Furthermore, as the accuracy of identifying the cause of death of a corpse improves, for example, if a body suspected to have died of internal causes turns out to have died of external causes, the police can begin an investigation with the possibility of foul play in mind. This will likely reduce the chances of a crime being overlooked.

In addition, in the analysis device 2 according to this embodiment, the first analysis result obtained by the analysis processing function 20c and the second analysis result obtained by the integration processing function 20d are stored in the analysis result storage circuit 30c in the information storage circuit 30 and saved as a database. For example, the condition of a corpse varies greatly depending on the time since death and weather conditions. For example, even if the corpse is the same 24 hours since death, if the temperature around the corpse is high, decomposition will progress quickly, but if the temperature is low, decomposition will not progress as much. The condition of the corpse will also vary depending on the humidity around the corpse, and the presence or absence of wind and its strength.

For this reason, the standard corpse construction function 20g of the control circuit 20 organizes the images by body part stored in the body part image storage circuit 30b, the first analysis results obtained by the analysis processing function 20c, and the second analysis results obtained by the integration processing function 20d according to the subject classification conditions that include at least one of the time since death and weather conditions for each body part, to construct a "standard corpse." A "standard corpse," which is a standard corpse classified according to the subject classification conditions, is a major clue when identifying the cause of death based on the corpse, and is thought to contribute to improving the accuracy of identifying the cause of death in the future. Furthermore, information about such a "standard corpse" is thought to contribute to improving the analysis accuracy of the analysis processing function 20c and the integration processing function 20d.

As described above, the corpse of the subject is divided into parts before images of the corpse are taken, and the analysis processing function 20c performs an analysis of the cause of death for each part based on these images, which makes it easier for the analysis processing function 20c to narrow down the points to be analyzed. Furthermore, when the integration processing function 20d further analyzes the first analysis results obtained by multiple different types of analysis processing, it is possible to systematically determine the reliability of the first analysis results and the presence or absence of inconsistencies. As a result, it becomes easier to identify the true cause of death of the corpse. It is also believed that the processing time required for the integration processing function 20d to make a determination can be shortened.

In this embodiment, the head analysis function 20c1, neck analysis function 20c2, chest analysis function 20c3, abdominal analysis function 20c4, and limb analysis function 20c5 constitute a plurality of different types of analysis processing units that obtain a first analysis result related to the cause of death, and the integration processing function 20d in this embodiment constitutes an integration processing unit that obtains a second analysis result related to the cause of death.

The first output function 20e in this embodiment constitutes a first output unit that outputs the second analysis result, and the second output function 20f in this embodiment constitutes a second output unit that outputs the indecision information. The image addition determination function 20b in this embodiment constitutes an image addition determination unit that outputs an instruction to add an image when it is determined that an image is insufficient.

In addition, the analysis result storage circuit 30c in this embodiment constitutes an analysis result storage unit that outputs the first analysis result and the second analysis result, and the standard corpse construction function 20g in this embodiment constitutes a standard corpse construction unit that constructs a standard corpse under the subject classification conditions.

Although several embodiments have been described above, these embodiments are presented only as examples and are not intended to limit the scope of the invention. The novel device and method described in this specification can be implemented in various other forms. For example, the image capturing device may be an MRI. Also, a dual energy CT that captures CT scans using two types of X-rays with different tube voltages may be used. Also, detailed examinations may be autopsies by a pathologist. Also, various omissions, substitutions, and modifications may be made to the forms of the device and method described in this specification without departing from the gist of the invention. The appended claims and their equivalents are intended to include such forms and modifications that are within the scope and gist of the invention.

1...analysis system, 2...analysis device, 10...image capturing device, 12...external information storage device, 20...control circuit, 20a...image acquisition function, 20b...image addition determination function, 20c...analysis processing function, 20c1...head analysis function, 20c2...neck analysis function, 20c3...chest analysis function, 20c4...abdominal analysis function, 20c5...limb analysis function, 20d...integration processing function, 20e...first output function, 20f...second output function, 20g... Standard corpse construction function, 22... program storage circuit, 24... display unit, 26... input unit, 28... communication unit, 30... information storage circuit, 30a... death chart storage circuit, 30b... part-specific image storage circuit, 30b1... head database, 30b2... neck database, 30b3... chest database, 30b4... abdomen database, 30b5... limbs database, 30b6... database management circuit, 30c... analysis result storage circuit

Claims (10)

A plurality of different types of analysis processing units that obtain a plurality of first analysis results related to a cause of death based on information on the subject;
an integration processing unit that obtains a second analysis result, which is information that assists in identifying a cause of death of the subject, by using the presence or absence of a contradiction in the plurality of first analysis results obtained by the plurality of analysis processing units;
An analysis device comprising: A plurality of different types of analysis processing units that obtain a plurality of first analysis results related to a cause of death based on information on the subject;
an integration processing unit that obtains a second analysis result, which is information that assists in identifying a cause of death of the subject, based on the plurality of first analysis results;
An analysis device comprising:
The integration processing unit also calculates a value representing a strength of validity of the second analysis result . The analysis device according to claim 1 , wherein the integration processing unit determines a second analysis result based on the reliability of the first analysis results determined by the plurality of analysis processing units. The analysis device according to claim 1 , further comprising a first output unit that outputs the second analysis result. The analysis device according to claim 1 , wherein the integration processing unit generates indecision information when the cause of death cannot be identified based on the plurality of first analysis results. The analysis device according to claim 5 , further comprising a second output section that outputs the undecidable information. The apparatus further includes a region-specific image storage unit in which images of the subject are stored by region,
7. The analysis device according to claim 1, wherein each of the different types of analysis processing units acquires an image of a corresponding part from the part-specific image storage unit, and determines the first analysis result based on the acquired image of the corresponding part. The analysis device according to claim 7 , wherein each of the plurality of analysis processing units determines the first analysis result based on external information including, in addition to the image of the corresponding body part, at least one of the following : whether or not cardiopulmonary resuscitation was performed, time since death, weather information, and symptoms complained of during life. The analysis device according to claim 7 or 8, further comprising an image addition determination unit that, when a subject is present in an image capturing device that captures an image of the subject, determines whether the multiple analysis processing units have captured images necessary to obtain the first analysis result using the image capturing device, and outputs an instruction to add images if it is determined that there are insufficient images. an analysis result storage unit that stores the first analysis result and the second analysis result;
A standard corpse construction unit that classifies subjects based on subject classification conditions including at least one of postmortem time and weather conditions, and constructs standard corpses for each of the subject classification conditions;
The analysis device according to claim 1 , further comprising:

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