Information processing apparatus, imaging apparatus, information processing method and program

Abstract

To solve the problem in which a medical doctor cannot efficiently search a necessary image in communication with a patient.SOLUTION: An information processing apparatus comprises: acquisition means that acquires medical information of a patient on the basis of patient identification information associated with an image of the patient; and calculation means that calculates importance of the image in communication with the patient on the basis of the medical information.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an imaging device, an information processing method, and a program. [Background technology]

[0002] In medical settings where cameras are used to capture images of affected areas, doctors and other medical professionals often show the images to patients while communicating with them, such as explaining the purpose and content of the treatment. In such cases, doctors search through a large number of images to find the ones they need for communication.

[0003] Generally, when searching for images, it is possible to search and select images based on the shooting date and time, shooting location, etc. Furthermore, Patent Document 1 discloses a technology for determining the display order of deletion candidates for multiple image data based on attribute information such as the size of the image data, ISO sensitivity, and amount of camera shake. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 5067213 Summary of the Invention [Problem to be solved by the invention]

[0005] However, images that are important for doctors to communicate with patients and images that are unnecessary do not necessarily correspond to the image capture date, attribute information of the image data, etc. Therefore, doctors cannot efficiently search for images that are necessary for communication with patients.

[0006] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide an information processing device, an imaging device, an information processing method, and a program that can improve the efficiency of image retrieval in communication between doctors and patients. [Means for solving the problem]

[0007] In order to solve this problem, for example, an information processing device of the present invention has the following arrangement: an acquisition means for acquiring medical information of a patient based on patient identification information associated with an image of the patient; a calculation means for calculating the importance of the image in communication with the patient based on the medical information; It has. [Effects of the Invention]

[0008] According to the present invention, it is possible to provide an information processing device, an imaging device, an information processing method, and a program that can improve the efficiency of image retrieval in communication between a doctor and a patient. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing the device configuration of a medical system according to an embodiment. [Figure 2] FIG. 1 is a block diagram showing a hardware configuration of an imaging apparatus according to an embodiment. [Figure 3] FIG. 4 is a flowchart of importance calculation processing according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of a display screen of images based on importance according to the first embodiment. [Figure 5] FIG. 4 is a diagram of an addition table for calculating importance according to the first embodiment. [Figure 6] FIG. 10 is a flowchart of importance calculation processing according to the second embodiment. [Figure 7] FIG. 10 is a diagram of a weighting table for calculating importance according to the second embodiment. [Figure 8] FIG. 11 is a flowchart of importance calculation processing according to the third embodiment. [Figure 9] FIG. 11 is a diagram of a weighting table for calculating importance according to the third embodiment. [Figure 10] FIG. 13 is a flowchart of importance calculation processing according to the fourth embodiment. [Figure 11]FIG. 13 is a diagram of a weighting table for calculating importance according to the fourth embodiment. [Figure 12] FIG. 13 is a flowchart of image deletion processing according to the fifth embodiment. [Figure 13] FIG. 13 is a diagram showing an example of a display screen for images that are candidates for deletion according to the fifth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the invention claimed. Although multiple features are described in the embodiments, not all of these multiple features are necessarily essential to the invention, and multiple features may be combined arbitrarily. Furthermore, in the accompanying drawings, the same reference numerals are used to designate the same or similar components, and redundant explanations will be omitted.

[0011] [System Configuration] 1 is a diagram showing the device configuration of a medical system according to an embodiment, which will be described with reference to FIG.

[0012] The medical system includes a medical information management device 102, an electronic medical record terminal device 103, an image management device 104, a medical system control device 105, and an imaging device 106. The medical information management device 102, the electronic medical record terminal device 103, the image management device 104, the medical system control device 105, and the imaging device 106 are connected to a network 101.

[0013] The network 101 enables the transmission and reception of information between devices. The network 101 performs wireless data transmission, wired data transmission, and various controls in information communication. The network communication protocol may be Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Picture Transfer Protocol (PTP), Universal Serial Bus (USB), Local Area Network (LAN), Health Level Seven (HL7), Digital Imaging and Communications in Medicine (DICOM), etc. The communication protocol may be any other protocol as long as it can communicate image data, text, control data, etc.

[0014] The medical information management device 102 stores and manages, as medical information, in-hospital patient information (e.g., patient ID (patient identification information), name, medical department, age, gender, medical history, past medical treatment history, etc.), doctor information (e.g., doctor ID, name, department affiliation information, etc.), medical system, and clinical path. The patient information includes at least one of the disease name, disease type, severity, and affected area status. The affected area status may be included in the clinical path. The medical information management device 102 verifies and authenticates the doctor's login and logoff information to the electronic medical record terminal device 103, provides doctor information, and provides patient information in the form of an electronic medical record. The medical information management device 102 also stores updated data. The medical information management device 102 may also update and store setting information, such as the imaging settings of the imaging device 106, for each department and doctor information. Such a medical information management device 102 is registered in a personal computer, an in-hospital server, or a cloud server. Therefore, other devices can access the medical information management device 102 via the network 101 when necessary.

[0015] At the time of examination, the electronic medical record terminal device 103 downloads information about the logged-in doctor and the patient to be examined from the medical information management device 102 described above, and provides, displays, edits, and updates the electronic medical record function.

[0016] The image management device 104 functions as an image server that manages image data, which is data on patient images. Note that the term "image" may include both images and image data. The image management device 104 stores, updates, and deletes images, as well as the photographer information and patient identification information associated with the images, and references the data as needed. The image management device 104 may be provided for each department within a hospital, or may be installed on an external network such as the cloud.

[0017] The medical system control device 105 is connected to the hospital's data server, control management system, etc. The medical system control device 105 transmits and receives information such as various management information, setting information, information updates, and control information of the hospital's systems to the medical information management device 102, electronic medical record terminal device 103, image management device 104, and imaging device 106 as needed.

[0018] The imaging device 106 is an example of an information processing device, and captures an image of a subject such as a patient and generates image data.

[0019] In this embodiment, the entire system is described assuming that the medical information management device 102, the electronic medical record terminal device 103, the image management device 104, the medical system control device 105, and the imaging device 106 are each separate devices, but the functions of two or more devices may be realized by a single device, such as by constructing two or more of the medical information management device 102, the electronic medical record terminal device 103, the image management device 104, the medical system control device 105, and the imaging device 106 in the same housing. In this way, a system with appropriate cost can be configured in accordance with the load and capacity required by the medical system.

[0020] [Imaging device] Fig. 2 is a block diagram showing the hardware configuration of the imaging device 106 of this embodiment. The imaging device 106 of this embodiment will be described using Fig. 2. The imaging device 106 is an example of an information processing device, and executes predetermined control programs and processing programs to perform processing described below. The imaging device 106 has a CPU 201, a ROM 202, a RAM 203, a display unit 204, an imaging unit 205, an operation unit 206, an image processing unit 207, a storage medium I / F 208, a network I / F 210, and a system bus 212.

[0021] The CPU 201 is an abbreviation for Central Processing Unit and is an arithmetic processing device that controls the system. Instead of or in addition to the CPU 201, the image capture device 106 may include other processors such as an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), or a QPU (Quantum Processing Unit). Some or all of the functions of the image capture device 106 are realized by one or more processors including the CPU 201 reading out a program stored in the ROM 202 or the storage medium 209, expanding the program into the RAM 203, and executing the program. The CPU 201 is an example of an acquisition unit, a calculation unit, and a display unit. Some or all of the functions of the image capture device 106 may also be realized by one or more circuits, such as an ASIC (Application Specific Integrated Circuit) and a PLD (Programmable Logic Device) including an FPGA (Field Programmable Gate Array).

[0022] ROM 202 is an abbreviation for Read Only Memory, and is a non-volatile storage device that stores the operation processing procedures of CPU 201 (for example, programs for computer startup processing and basic input / output processing, etc.).

[0023] The RAM 203 is an abbreviation for Random Access Memory, and functions as the main memory of the CPU 201. Various programs, including control programs for implementing the processes described below, are loaded into the RAM 203 from the ROM 202, the storage medium 209, etc., and executed by the CPU 201. The RAM 203 provides a work area when the CPU 201 executes various processes.

[0024] The display unit 204 is a display such as a liquid crystal display device, an organic EL (Electro Luminescence) display device, etc. The display unit 204 displays various images under the control of the CPU 201.

[0025] The imaging unit 205 has a lens, an imaging element, etc. The imaging unit 205 captures an image of a subject and outputs the image data obtained by converting light into an electrical signal.

[0026] The operation unit 206 is an input device for receiving user operations and includes a character information input device such as a keyboard, a pointing device such as a mouse or a touch panel, a button, a dial, a joystick, a touch sensor, a touch pad, and the like.

[0027] Based on the control of the CPU 201, the image processing unit 207 performs various image processing on image data stored in the non-volatile memory ROM 202 and storage medium 209, image data acquired via the network I / F 210, and captured image data.

[0028] The storage medium I / F 208 is an interface into which a storage medium 209 is attached. Based on the control of the CPU 201, the storage medium I / F 208 reads data from the attached storage medium 209 and writes data to the storage medium 209. The storage medium 209 may be a non-volatile storage device such as a memory card, a CD (Compact Disc), a DVD (Digital Versatile Disc), an HDD (Hard Disk Drive), or an SSD (Solid State Drive).

[0029] The network I / F 210 is a network interface (communication means) and is connected to a computer network 211 via a wireless or wired communication line. Data is sent and received from devices that can communicate with the network I / F 210.

[0030] The system bus 212 includes an address bus, a data bus, a control bus, and the like, and connects units including the CPU 201 and the network I / F 210 .

[0031] [Importance calculation process flow] FIG. 3 is a flowchart of the importance calculation process for calculating the importance of an image according to the first embodiment. The importance is the level of importance in communication between a medical professional, such as a doctor, and a patient. For example, an image to be presented to a patient by a medical professional at the next examination has a higher importance level. That is, among multiple images of an affected area, the images to be presented to the patient by a medical professional at the next examination are prioritized, and the affected area image with the highest priority is set as the affected area image with the highest importance level. The importance calculation process is executed, for example, by the imaging device 106. The importance calculation process is executed after an image of the patient's affected area is captured or when the affected area image is stored in the image management device 104. Each step in FIG. 3 will be described in detail below.

[0032] In step S301, the CPU 201 acquires an image from the image management device 104 via the storage medium 209 or the network I / F 210. The image is an image (image data) obtained by the imaging unit 205 or the like capturing an image of an affected area of ​​a patient.

[0033] In step S302, the CPU 201 acquires patient identification information associated with the image data (image). The patient identification information is, for example, added to the image data as meta information. The added patient identification information may be patient identification information selected by the photographer from a patient list displayed on the image capture device 106. Alternatively, the added patient identification information may be patient identification information acquired by the image capture device 106 reading a short-range wireless communication tag of the patient. In this case, the image capture device 106 may capture a barcode or the like corresponding to the patient identification information and then transmit the barcode to the medical information management device 102 via the network I / F 210. Furthermore, the image capture device 106 may receive patient identification information acquired by the medical information management device 102 by analyzing the barcode, and add the patient identification information to the image data.

[0034] In step S303, the CPU 201 acquires medical information linked to the patient or image data from the medical information management device 102 based on the acquired patient identification information. Items of medical information are items necessary for acquiring the accrual table in the next step S304, such as the disease name, severity of the affected area, and affected area status. The affected area status is the status of the progression and recovery of the disease. The affected area status may be set separately for the acute phase, recovery phase, and chronic phase, or may be set in more detail according to each state of the disease (such as surgery, type of treatment, type of medication, and amount of medication).

[0035] In step S304, the CPU 201 acquires the addition table via the network I / F 210. As shown in Fig. 5, the addition table has an addition value set for each item of medical information. The addition table is stored in, for example, the medical information management device 102.

[0036] In step S305, the CPU 201 calculates the importance of the image in communication between the doctor and the patient (hereinafter referred to as "importance") by referring to the acquired medical information and the addition table. Details of this step will be described later with reference to FIG.

[0037] In step S306, the CPU 201 determines and stores the importance level based on the result calculated in step S305. The importance level may be added to the image as meta information, may be stored in the storage medium 209, or may be stored in a storage unit or database (not shown) of the image management device 104.

[0038] Thereafter, the CPU 201 performs processing based on the importance of the image. For example, the CPU 201 may set a threshold value for the importance and display only images whose importance is equal to or greater than the threshold value on the display unit of the imaging device 106. This improves the efficiency of image searches when doctors communicate with patients.

[0039] 4 is a diagram showing an example of a display screen for images based on the importance level according to the first embodiment. The screen is displayed on the display unit 204 of the imaging device 106. Display of images based on the importance level will be described with reference to FIG.

[0040] 4(a) displays thumbnails of captured images on the display unit 204. As shown in FIG. 4(a), the CPU 201 may add a marking 401 to images whose importance is equal to or greater than a threshold and display them on the display unit 204. This improves the efficiency of image searches when doctors communicate with patients.

[0041] 4(b), the CPU 201 may arrange images in order of importance within the same disease and display them in the thumbnail 404. This allows a user such as a doctor to efficiently display a desired image in the enlarged display section 405 by using the image forwarding buttons 402 and 403. Alternatively, if images from the imaging device 106 are displayed in the thumbnail 404 in order of decreasing importance, a user such as a doctor can efficiently select unnecessary images when, for example, deleting image data stored in the storage medium 209.

[0042] In this embodiment, the imaging device 106 is described as executing the importance calculation process, but an information processing device other than the imaging device 106, such as the medical information management device 102, may also perform the importance calculation process and display the image on the electronic medical record terminal device 103 based on the importance.

[0043] [Importance calculation process flow] 5 is a diagram of an addition table for calculating the importance. A specific calculation of the importance will be described with reference to FIG.

[0044] When doctors communicate with patients, they often use images of the affected area to explain progress, serious illnesses, and intractable diseases. This allows patients to visually confirm changes in their condition and deepen their understanding. The surcharge table reflects progress and the severity of the disease.

[0045] The additional charge table 501 shown in Figure 5(a) is a table of additional charges added according to the type of disease indicated by the disease name. In the additional charge table 501, additional charges are set according to the ease with which the disease changes. Specifically, in the additional charge table 501, the additional charge is smaller for diseases that are difficult to change and require long-term treatment, such as warts and athlete's foot.

[0046] The additional charge table 502 shown in FIG. 5(b) is a table having additional charges according to the type of disease indicated by the disease name. In the additional charge table 502, additional charges are set according to the severity of the disease and the difficulty of treatment. Specifically, in the additional charge table 502, the additional charge is higher for serious and incurable diseases such as life-threatening diseases and diseases that are difficult to cure. Also, in the additional charge table 502, the additional charge is higher for diseases that are difficult to treat, such as designated incurable diseases such as pemphigus. On the other hand, in the additional charge table 502, the additional charge is lower for diseases that are easy to treat, such as prurigo and eczema, which heal naturally.

[0047] In this embodiment, two addition tables 501 and 502 according to the type of disease are used for explanation, but it is also possible to combine the tendency of the disease's course to change and the severity of the disease into one addition table.

[0048] The addition table 503 is a table in which the addition value changes depending on the severity. In addition table 503, as in addition table 502, the addition value increases for severity that is life-threatening.

[0049] The additional charge table 504 is a table in which the additional charge value changes depending on the status of the affected area of ​​the disease. In the additional charge table 504, the additional charge value changes depending on whether or not the period is one in which the disease has progressed or changed. In the additional charge table 504, for example, the changes in the affected area are significant during the acute phase, such as immediately before and after surgery, so the additional charge value for that period is large. On the other hand, the additional charge value is small during the chronic phase, when there is no change, and during periods when there is almost no progress, such as after treatment is completed. These affected area statuses can be obtained from the clinical pathway to change the additional charge in detail.

[0050] A clinical path shows a step-by-step plan of treatment (treatment, examinations, etc.) until a target state is reached, and by performing treatment according to the clinical path, the treatment content is standardized, which increases the understanding of medical staff and patients. By referring to the clinical path, the treatment and treatment content are aligned with the status of the affected area, so additional values ​​can be set in detail for each item on each date of the clinical path.

[0051] Here, the sum is assumed to be X1 obtained from addition table 501, X2 obtained from addition table 502, X3 obtained from addition table 503, and X4 obtained from addition table 504. CPU 201 uses the sums to calculate importance V1 as V1=X1+X2+X3+X4 and saves it.

[0052] The flow of the importance calculation process in the first embodiment has been described above.

[0053] As described above, this embodiment calculates the importance of an image to a patient based on medical information, which allows users such as doctors to search for images based on the importance, thereby improving the efficiency of user image searches.

[0054] In this embodiment, images are displayed based on importance, so doctors can easily search for images necessary for communication with patients based on the displayed images.

[0055] (Second embodiment) Communication between doctors and patients is primarily conducted during medical examinations. Images of patients are likely to be used during medical examinations or when a medical examination is scheduled. Furthermore, when a patient has already been treated and no medical examination is scheduled, images of patients are rarely used in communication. In particular, when communication takes place in a hospital ward and the doctor does not have the electronic medical record terminal device 103 at hand, the doctor often communicates using the display unit 204 of the imaging device 106. Therefore, the doctor needs to save images in the storage medium 209 of the imaging device 106. Whether or not images should be saved in the storage medium 209 of the imaging device 106 can be determined based on the medical system status, such as whether the patient is scheduled for examination and where the examination will be held. In the second embodiment, the medical system status is acquired from patient identification information associated with the image, and the importance of the image is calculated based on the medical system status.

[0056] The processing flow of the second embodiment is to accept an image display mode such as displaying a single image or displaying a list of images, and then perform an importance correction process for each image to be displayed (for example, all images in the storage medium 209). FIG. 6 is a flowchart of the importance calculation process of the second embodiment. Each step of the processing of the second embodiment will be described with reference to FIG. 6. Note that explanations of steps that are the same as those in the first embodiment (with the same step symbols) will be omitted, and new steps will be described. FIG. 7 is a diagram of a weighting table for calculating importance in the second embodiment.

[0057] In step S601, the CPU 201 continues to perform the subsequent steps until the importance correction process has been performed on all images in the storage medium 209, that is, if the number of remaining images that have not yet been corrected is greater than 0.

[0058] In step S602, the CPU 201 acquires the communication importance V1 of the image acquired in step S301 from the meta information or the storage medium 209.

[0059] In step S603, the CPU 201 acquires the medical system status of the patient from the medical information management device 102 based on the patient identification information in step S302.

[0060] In step S604, the CPU 201 acquires a weighting table 700 based on the medical system status shown in FIG. 7. The weighting table 700 is stored, for example, in the medical information management device 102, and the CPU 201 acquires the weighting table 700 via the network I / F 210. The weighting table 700 is a table in which weighting coefficients are associated with medical systems such as currently under examination, currently hospitalized, receiving home nursing care, undergoing rehabilitation, and scheduled to visit the hospital for treatment. The medical system status is not the medical system status at the time of image capture of the patient, but the current medical system status of the patient. If the patient is currently under examination, the doctor and patient are likely to communicate, and if the patient is hospitalized, the likelihood of communication is second highest. On the other hand, if the patient has already been treated, the likelihood of communication is low. If the patient is not currently under examination but is scheduled to visit the hospital, the likelihood of communication is somewhere in between.

[0061] In step S605, the CPU 201 refers to the weighting table 700 acquired in step S604 and determines the weighting coefficient α corresponding to the patient's medical system status acquired in step S603.

[0062] In step S606, the CPU 201 multiplies the importance V1 by the weighting coefficient α to calculate and determine the importance V2 (=α×V1).

[0063] The flow of the importance weighting process in the second embodiment has been described above.

[0064] In this embodiment, the processing is described as being performed by the imaging device 106, but the processing of this embodiment may be performed by an information processing device other than the imaging device 106, such as the medical information management device 102.

[0065] In the second embodiment, the importance of communication is corrected by a weighting coefficient according to the medical system status of the patient, so that the importance can be calculated with higher accuracy in line with the medical system status.

[0066] (Third embodiment) When an image is used in communication, there is a high possibility that related images will also be used for comparison, etc. In the third embodiment, when the imaging device 106 accepts an image display mode, the importance value of the image is weighted based on the importance of images related to the image, and the importance is corrected and calculated based on the weighting.

[0067] The processing flow of the third embodiment is to accept an image display mode such as displaying a single image or displaying a list of images, and then perform a correction process for the importance of each image to be displayed (for example, all images in the storage medium 209). FIG. 8 is a flowchart of the importance calculation process of the third embodiment. Each step of the processing of the third embodiment will be described with reference to FIG. 8. Note that explanations of steps that are the same as those in the above-mentioned embodiments (with the same step symbols) will be omitted, and new steps will be described. FIG. 9 is a diagram of a weighting table for calculating the importance of the third embodiment.

[0068] In step S801, the CPU 201 determines whether there are any related images related to the target image. Here, the related images are, for example, images of the same patient and the same disease. The CPU 201 acquires medical information related to images of the same patient and the same disease from the medical information management device 102. Here, the related images are described as images of the same patient and the same disease, but they may also be images of the same disease but the same site, or images of different diseases but related to complications (other diseases that may occur as a result of the disease). If the CPU 201 determines that there are no related images, it proceeds to step S805 and determines importance V3 = V1. If the CPU 201 determines that there are related images, it proceeds to step S802.

[0069] In step S802, the CPU 201 obtains the maximum value of the importance V1 of the related images. The CPU 201 obtains the importance V1 of the first embodiment for all of the related images and obtains the maximum value of the importance V1.

[0070] In step S803, CPU 201 obtains a weighting table 900 based on the maximum value of the importance of related images. As shown in Fig. 9, weighting table 900 is set so that the weighting coefficient increases as the maximum value of the importance of related images increases.

[0071] In step S804, the CPU 201 determines a weighting factor β from the weighting table 900 based on the maximum value of the importance of the related images.

[0072] In step S805, the CPU 201 calculates and determines the importance V3 (=β×V1) by multiplying the importance V1 by the weighting coefficient β.

[0073] In the third embodiment, weighting was performed using a weighting table 900 based on the maximum value of the importance of related images, but the weighting table may be based only on the average importance of related images and an additive value related to specific medical information. Furthermore, a weighting coefficient α based on the medical system status described in the second embodiment may be added, so that V3 = β × α × V1. This changes the order of importance among images within a patient.

[0074] The flow of the importance calculation process in the third embodiment has been described above.

[0075] In this embodiment, the processing is described as being performed by the imaging device 106, but the processing of this embodiment may be performed by an information processing device other than the imaging device 106, such as the medical information management device 102.

[0076] In the third embodiment, the importance of communication is corrected by a weighting coefficient according to the importance of related images, so that it is possible to calculate the importance more accurately in line with the importance of related images.

[0077] (Fourth embodiment) In the fourth embodiment, when the imaging device 106 receives an image display mode, if there are multiple images of the same patient with the same disease and the same affected area status, the importance values ​​are weighted.

[0078] Among related images, images with the same affected area status generally tend to show little change, even if they were taken on different days. However, when displaying images in order of importance, for example, if there are many images with the same affected area status, it becomes difficult to display images with other statuses. This situation is inconvenient when doctors and patients communicate by comparing progress. Even if images with the same affected area status span multiple days, displaying only representative images is sufficient for communication. Therefore, it is preferable to set the importance of images with the same affected area status on different days to a low level.

[0079] Fig. 10 is a flowchart of the importance calculation process in the fourth embodiment. Each step of the process in the fourth embodiment will be described with reference to Fig. 10. Note that explanations of steps that are the same as those in the above-mentioned embodiments (with the same step symbols) will be omitted, and new steps will be described. Fig. 11 is a diagram of a weighting table for calculating importance in the fourth embodiment.

[0080] In step S1001, the CPU 201 determines whether the acquired related images include an image with the same affected area status. If the CPU 201 determines that the related images include the same affected area status, the CPU 201 proceeds to step S1002. If the CPU 201 determines that the related images do not include the same affected area status, the CPU 201 proceeds to step S1004 and determines importance V4=V1.

[0081] In step S1002, the CPU 201 acquires a weighting table 1100. As shown in FIG. 10, the weighting table 1100 includes weights set in the order of the imaging dates of images of the same affected area status. The "oldest," "first different date," "second different date," "third different date," and "latest" in the weighting table 1100 represent the order of the imaging dates. For example, in the case of a chronic phase status in which the condition of the affected area hardly changes, the weighting coefficients of images other than the most recent image are uniformly set low to lower their importance. In addition, in the case of a recovery phase status in which the change in the affected area improves as expected, the weighting coefficients of the most recent and oldest images may be set to higher importance. Furthermore, in the case of an acute phase status in which the change in the affected area is expected to be significant even within the same affected area status, weighting is unnecessary, and therefore the weighting coefficients may be set uniformly (for example, to 1). In addition, in any affected area status, the most recent weighting coefficient may be set to 1 or the maximum value.

[0082] In step S1003, the CPU 201 determines a weighting coefficient γ by referring to the weighting table 1100 based on the affected area status and the image capture date.

[0083] In step S1004, the CPU 201 multiplies the importance V1 by the weighting coefficient γ to calculate and determine the importance V4 (=γ×V1).

[0084] The weighting based on the medical system status described in the second embodiment and the weighting based on the importance of the related image described in the third embodiment may be combined to calculate the importance V4 = γ × β × α × V1. Alternatively, the weighting based on the medical system status described in the second embodiment and the weighting based on the importance of the related image described in the third embodiment may be combined.

[0085] The flow of the importance calculation process in the fourth embodiment has been described above.

[0086] Although the present embodiment has been described as processing by the imaging device 106, the processing of this embodiment may be performed by an information processing device other than the imaging device 106, such as the medical information management device 102, for example.

[0087] In the fourth embodiment, the importance of communication is corrected by a weighting coefficient according to the affected area status, so that it is possible to calculate the importance more accurately according to the affected area status.

[0088] (Fifth embodiment) In the fifth embodiment, images that are candidates for deletion are presented to a user such as a doctor based on the calculated importance. FIG. 12 is a flowchart of the image deletion process in the fifth embodiment. FIG. 13 is a diagram showing an example of a display screen for images that are candidates for deletion in the fifth embodiment. Each step of the process in the fifth embodiment will be described with reference to FIG. 12. Note that explanations of steps that are the same as those in the above-described embodiments (with the same step symbols) will be omitted, and new steps will be described.

[0089] In step S1201, the CPU 201 receives an image deletion display mode from a user such as a doctor, and transitions to the image deletion display mode.

[0090] After executing steps S302 and S303, the CPU 201 proceeds to step S1202.

[0091] In step S1202, the CPU 201 repeats steps S1203 to S1208 until an instruction to end the image deletion display mode is received.

[0092] In step S1203, the CPU 201 determines images to be calculated for importance. For example, the CPU 201 may determine images to be calculated in order of their capture date from among a plurality of images for which importance has not yet been calculated.

[0093] In step S1204, the CPU 201 calculates the importance of the image determined as the calculation target. The calculation method of the importance may be any of the calculation methods in the above-described embodiments.

[0094] In step S1205, the CPU 201 determines whether the importance of the image to be processed is low. For example, the CPU 201 may compare the importance with a predetermined threshold to determine whether the importance is low. The threshold is not particularly limited and may be set as appropriate, for example, based on previously deleted images. As an example, the threshold may be set so that images in the chronic phase are determined to have low importance. If the CPU 201 determines that the importance of the image to be processed is not lower than the threshold and has not accepted termination of the deletion candidate display mode, the process proceeds to step S1203. On the other hand, if the CPU 201 determines that the importance of the image to be processed is lower than the threshold, the process proceeds to step S1206.

[0095] In step S1206, the CPU 201 displays the image to be processed as a deletion candidate on the display unit 204. For example, as shown in FIG. 13, the CPU 201 may display selection buttons 1302 and 1303 together with an image 1301 that is a deletion candidate. The CPU 201 may also display medical information about the patient. If a user such as a doctor wishes to delete the image 1301, the user selects the "Yes" selection button 1302, and if not, the user selects the "No" selection button 1303.

[0096] In step S1207, CPU 201 determines whether or not a deletion instruction for an image candidate for deletion has been received. If the user has selected select button 1303 and has not received an instruction to end the deletion candidate display mode, CPU 201 transitions to step S1203. On the other hand, if the user has selected select button 1302, CPU 201 transitions to step S1208.

[0097] In step S1208, the CPU 201 deletes the image candidate for deletion from the storage medium 209 or the image management device 104 from which the image was acquired.

[0098] Thereafter, the CPU 201 repeats step S1203 and subsequent steps until it receives an instruction from the user to end the deletion candidate display mode.

[0099] The flow of the image deletion process in the fifth embodiment has been described above.

[0100] In this embodiment, the processing is described as being performed by the imaging device 106, but the processing of this embodiment may be performed by an information processing device other than the imaging device 106, such as the medical information management device 102.

[0101] As described above, in the fifth embodiment, images that are candidates for deletion are displayed and presented to the user based on their importance, thereby making the image deletion process more efficient than when selecting images to delete from all images.

[0102] (Other embodiments) The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and having one or more processors in the computer of the system or device read and execute the program.The present invention can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

[0103] The disclosure of this specification includes the following information processing device, imaging device, information processing method, and program. (Item 1) an acquisition means for acquiring medical information of a patient based on patient identification information associated with an image of the patient; a calculation means for calculating the importance of the image in communication with the patient based on the medical information; An information processing device comprising: (Item 2) The acquisition means acquires the image of the patient from either an image server or a storage medium. 2. The information processing device according to item 1, (Item 3) The acquiring means acquires the medical information from a medical system in a hospital. 3. The information processing device according to item 1 or 2, (Item 4) The medical system includes at least one of an electronic medical record terminal device that provides an electronic medical record function, a medical information management device that stores medical information including clinical paths, and a medical system control device that transmits and receives information about the medical system. 4. The information processing device according to item 3, (Item 5) The medical information includes at least one of the type of disease, severity, affected area status, and medical system. 5. The information processing device according to claim 1, wherein: (Item 6) The acquisition means acquires the affected area status from a clinical pathway. 6. The information processing device according to item 5, (Item 7) The calculation means calculates the importance based on an added value corresponding to the medical information. 7. The information processing device according to claim 1, wherein: (Item 8) The calculation means corrects the importance based on a weighting coefficient corresponding to the medical system included in the medical information. 8. The information processing device according to any one of items 1 and 7, characterized in that: (Item 9) The calculation means corrects the importance based on a weighting coefficient corresponding to the importance of a related image related to the image. 9. The information processing device according to any one of items 1 and 8, characterized in that: (Item 10) The calculation means corrects the importance based on a weighting coefficient corresponding to an imaging date of the same patient and affected area status of the same affected area as the image. 10. The information processing device according to any one of items 1 and 9, characterized in that: (Item 11) 11. The information processing device according to claim 1, further comprising a display unit that displays the image on a display unit based on the importance. (Item 12) the information processing device according to item 1; an imaging means for imaging a subject; An imaging device having the above configuration. (Item 13) acquiring medical information of the patient based on patient identification information associated with the patient image; a calculation step of calculating the importance of the image in communication with the patient based on the medical information; An information processing method comprising: (Item 14) 12. A program for causing a computer to function as each means of the information processing device according to any one of items 1 to 11.

[0104] The invention is not limited to the above-described embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]

[0105] 102 Medical information management device, 103 Electronic medical record terminal device, 104 Image management device, 105 Medical system control device, 106 Imaging device, 201 CPU, 205 Imaging unit, 209 Storage medium.

Claims

1. an acquisition means for acquiring medical information of a patient based on patient identification information associated with an image of the patient; a calculation means for calculating the importance of the image in communication with the patient based on the medical information; An information processing device comprising:

2. The acquisition means acquires the image of the patient from either an image server or a storage medium.

2. The information processing apparatus according to claim 1, wherein:

3. The acquiring means acquires the medical information from a medical system.

2. The information processing apparatus according to claim 1, wherein:

4. The medical system includes at least one of an electronic medical record terminal device that provides an electronic medical record function, a medical information management device that stores medical information including clinical paths, and a medical system control device that transmits and receives information about the medical system.

4. The information processing apparatus according to claim 3,

5. The medical information includes at least one of the type of disease, severity, affected area status, and medical system.

2. The information processing apparatus according to claim 1, wherein:

6. The acquisition means acquires the affected area status from a clinical pathway.

6. The information processing apparatus according to claim 5,

7. The calculation means calculates the importance based on an added value corresponding to the medical information.

2. The information processing apparatus according to claim 1, wherein:

8. The calculation means corrects the importance based on a weighting coefficient corresponding to the medical system included in the medical information.

2. The information processing apparatus according to claim 1, wherein:

9. The calculation means corrects the importance based on a weighting coefficient corresponding to the importance of a related image related to the image.

2. The information processing apparatus according to claim 1, wherein:

10. The calculation means corrects the importance based on a weighting coefficient corresponding to an imaging date of the same patient and affected area status of the same affected area as the image.

2. The information processing apparatus according to claim 1, wherein:

11. 2. The information processing apparatus according to claim 1, further comprising display means for displaying the image on a display unit based on the importance.

12. The information processing device according to claim 1 ; an imaging means for imaging a subject; An imaging device having the above configuration.

13. acquiring medical information of the patient based on patient identification information associated with the patient image; a calculation step of calculating the importance of the image in communication with the patient based on the medical information; An information processing method comprising:

14. A program for causing a computer to function as each of the means of the information processing device according to any one of claims 1 to 11.

Images