Medical image quality control method and device, electronic device and computer storage medium

Abstract

The present application provides a medical image quality control method, which is applied to a medical image reading system. The method includes: in response to the quality control review failure information of the initial medical image sequence corresponding to the subject, determining M medical images to be reviewed corresponding to the subject, wherein the quality control review failure information includes failed image information and failed review item information; based on the M medical images to be reviewed and the failed image information, determining N incremental images corresponding to the subject; based on the failed review item information, reviewing the N incremental images to update the quality control results corresponding to the initial medical image sequence. The IRC system uses the above-mentioned medical image quality control method to perform quality control on the medical images supplemented by the CRC, and performs repeated quality control reviews efficiently and in a targeted manner without the need for a full scan, effectively reducing system occupancy.

Description

Technical Field

[0001] The present application relates to the technical field of medical image interpretation, and in particular to a medical image quality control method and device, electronic equipment, and computer storage medium. Background Art

[0002] After the Clinical Research Coordinator (CRC) of the research center uploads the medical images collected by the imaging department to the Independent Review Center (IRC) system, to ensure the quality of the medical images viewed by the independent reviewer, the IRC system's automatic quality control program needs to perform a quality control review on the uploaded medical images. If the quality control review fails, a quality control review failure message will be sent to the research center so that the research center can upload additional medical images.

[0003] In the existing technology, the automatic quality control program of the IRC system merges the re-uploaded medical image with the original medical image for full scanning and then obtains an updated quality control result. However, the full scanning of the supplementary uploaded medical image occupies too many system resources, resulting in resource waste. Summary of the Invention

[0004] In view of this, the embodiments of the present application provide a medical image quality control method, a medical image quality control device, an electronic device and a computer-readable storage medium to solve the technical problem of waste of system resources caused by full scanning of supplementary uploaded medical images in the prior art.

[0005] According to a first aspect of an embodiment of the present application, a medical image quality control method is provided, which is applied to a medical image interpretation system. The method comprises: in response to quality control review failure information for an initial medical image sequence corresponding to a subject, determining M medical images corresponding to the subject to be reviewed, wherein the quality control review failure information includes failed image information and failed review item information; based on the M medical images to be reviewed and the failed image information, determining N incremental images corresponding to the subject; and reviewing the N incremental images based on the failed review item information to update the quality control results corresponding to the initial medical image sequence.

[0006] In one embodiment, determining M medical images to be reviewed corresponding to a subject includes: determining, based on P supplementary medical images uploaded, patient number information corresponding to each of the P supplementary medical images; for each of the P supplementary medical images, determining whether the patient number information corresponding to the supplementary medical image is the same as the subject number information corresponding to the subject; if not, deleting the supplementary medical image and sending first feedback information to the research center; if so, determining examination number information corresponding to the supplementary medical image, and further determining whether the supplementary medical image is a medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence.

[0007] In one embodiment, whether the supplementary medical image is a medical image to be reviewed is further determined based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence, including: judging whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence; if so, determining the supplementary medical image as a medical image to be reviewed; if not, determining the examination date information corresponding to the supplementary medical image, and based on the examination date information corresponding to the supplementary medical image and the examination date information corresponding to the initial medical image sequence, judging whether the supplementary medical image and the initial medical image sequence belong to the same examination window period; if they belong to the same examination window period, determining the supplementary medical image as a medical image to be reviewed; if they do not belong to the same examination window period, deleting the supplementary medical image, and sending second feedback information to the research center.

[0008] In one embodiment, based on M medical images to be reviewed and failed image information, N incremental images corresponding to the subject are determined, including: determining image sequence identification information corresponding to each of the M medical images to be reviewed; for each medical image to be reviewed in the M medical images to be reviewed, judging whether the image sequence identification information corresponding to the medical image to be reviewed is the same as the image sequence identification information corresponding to the initial medical image sequence; if not, determining the medical image to be reviewed as an incremental image; if so, determining the image identification information corresponding to the medical image to be reviewed, and further determining whether the medical image to be reviewed is an incremental image based on the image identification information corresponding to the medical image to be reviewed and the failed image information.

[0009] In one embodiment, based on the image identification information corresponding to the medical image to be reviewed and the failed image information, determining whether the medical image to be reviewed is an incremental image includes: determining the successful image information based on the failed image information and the initial medical image sequence; judging whether the image identification information corresponding to the medical image to be reviewed is the same as the image identification information corresponding to the successful image information; if so, deleting the medical image to be reviewed and sending third feedback information to the research center; if not, determining the medical image to be reviewed as an incremental image.

[0010] In one embodiment, based on the failed audit item information, N incremental images are audited to update the quality control results corresponding to the initial medical image sequence, including: for each incremental image in the N incremental images, based on the failed audit item information, the incremental image is quality-controlled scanned item by item to determine the scanning result of the incremental image; based on the scanning results corresponding to each of the N incremental images, the quality control results corresponding to the initial medical image sequence are updated.

[0011] In one embodiment, based on the scanning results corresponding to each of the N incremental images, the quality control results corresponding to the initial medical image sequence are updated, including: when the scanning results of the N incremental images are all qualified, deleting the quality control review failure information, and updating the quality control result to qualified; or, when the scanning result of at least one image among the N incremental images is unqualified, based on the unqualified items in the scanning results of the N incremental images, updating the quality control review failure information, and updating the quality control result to failure; based on the updated quality control review failure information, quality control is performed on the supplementary medical images uploaded again until the quality control result is qualified.

[0012] According to a second aspect of an embodiment of the present application, a medical image quality control device is provided, which is applied to a medical image reading system, and the device includes: a first determination module, configured to determine M medical images to be reviewed corresponding to the subject in response to quality control review failure information of an initial medical image sequence corresponding to the subject, wherein the quality control review failure information includes failed image information and failed review item information; a second determination module, configured to determine N incremental images corresponding to the subject based on the M medical images to be reviewed and the failed image information; and a third determination module, configured to review the N incremental images based on the failed review item information to update the quality control results corresponding to the initial medical image sequence.

[0013] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: a processor; and a memory, wherein computer program instructions are stored in the memory, and when the computer program instructions are executed by the processor, the processor executes the medical image quality control method as described in the first aspect above.

[0014] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the medical image quality control method as described in the first aspect above.

[0015] The medical image quality control method provided in the embodiment of the present application is applied to a medical image reading system. The medical image quality control method, in response to the quality control review failure information of the initial medical image sequence corresponding to the subject, determines M medical images to be reviewed belonging to the current examination of the subject in the medical images supplemented by the CRC; based on the failed image information, filters out the images that already exist in the IRC system among the M medical images to be reviewed, and obtains N incremental images corresponding to the subject; based on the failed review item information, repeats the quality control review of the N incremental images in a targeted manner to update the quality control results corresponding to the initial medical image sequence. Through the above-mentioned medical image quality control method, the IRC system can perform efficient and targeted repeated quality control reviews on the medical images supplemented by the CRC, without the need for a full scan, effectively reducing system occupancy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 FIG2 is a flow chart of a medical image quality control method provided in one embodiment of the present application.

[0017] Figure 2 FIG2 is a flow chart of a medical image quality control method provided in one embodiment of the present application.

[0018] Figure 3 FIG2 is a flow chart of a medical image quality control method provided in one embodiment of the present application.

[0019] Figure 4 FIG2 is a flow chart of a medical image quality control method provided in one embodiment of the present application.

[0020] Figure 5 FIG2 is a flow chart of a medical image quality control method provided in one embodiment of the present application.

[0021] Figure 6 FIG2 is a flow chart of a medical image quality control method provided in one embodiment of the present application.

[0022] Figure 7 FIG2 is a schematic structural diagram of a medical image quality control device provided in one embodiment of the present application.

[0023] Figure 8 FIG2 is a schematic structural diagram of a first determination module in a medical image quality control device provided in one embodiment of the present application.

[0024] Figure 9 FIG2 is a schematic structural diagram of a second determination module in a medical image quality control device provided in one embodiment of the present application.

[0025] Figure 10 FIG2 is a schematic structural diagram of a third determination module in a medical image quality control device provided in one embodiment of the present application.

[0026] Figure 11 Shown is a structural schematic diagram of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] In recent years, with the rapid development of medical imaging technology, IRC has become increasingly important in the field of drug clinical research. IRC refers to a professional supplier that provides independent third-party project evaluation services for clinical trial projects. In the IRC business process, the research center's CRC uploads medical images to the IRC system, and independent readers need to retrieve medical images from the IRC system for reading. However, the research center may not follow standard guidelines when taking images, resulting in the collected medical images being unreadable. For example, key parts of the subject are not photographed or the images taken are not standardized, resulting in the medical images being unreadable. In addition, CRCs cannot avoid misoperation during the image upload process, resulting in image omissions or incorrect transmission. Due to the existence of the above problems, independent readers are unable to read the images normally or fail to read the images, resulting in significant losses.

[0029] To ensure smooth, efficient, and cost-effective reading, the quality of the medical images viewed by independent readers must be guaranteed. Therefore, before independent readers begin their readings, the IRC system's automated quality control program conducts a quality control review of each uploaded medical image. For example, this review examines image completeness and the inclusion of key areas relevant to the clinical trial. If a quality control review fails, a failure notification is sent to the research center, allowing them to upload additional images.

[0030] However, in existing technologies, automatic quality control programs merge the re-uploaded medical image with the original medical image and perform a full scan (i.e., the merged image is still subject to quality control review according to all review items) to obtain updated quality control results. This automatic quality control program always performs a full scan of the supplementary uploaded medical image before generating a result, which consumes excessive system resources and results in resource waste.

[0031] In order to solve the above problems, an embodiment of the present application provides a medical image quality control method, so that when the quality control review fails, the IRC system can efficiently and targetedly repeat the quality control review of the medical images uploaded by the CRC, without the need for a full scan, effectively reducing system occupancy.

[0032] The following combination Figures 1 to 11 The medical image quality control method, medical image quality control device, electronic device and computer-readable storage medium mentioned in the embodiments of the present application are introduced in detail.

[0033] Exemplary medical image quality control method

[0034] Figure 1 The figure shows a flow chart of a medical image quality control method provided in one embodiment of the present application. The medical image quality control method provided in this embodiment of the present application is applied to a medical image reading system, and is used to perform quality control on medical images that are supplemented by the research center after the reading center has failed the review. The execution entity of the medical image quality control method provided in this embodiment of the present application is a server or computer in the IRC system.

[0035] like Figure 1 As shown, the medical image quality control method includes the following steps.

[0036] Step 101: In response to quality control review failure information of an initial medical image sequence corresponding to a subject, M medical images to be reviewed corresponding to the subject are determined.

[0037] Exemplarily, the quality control review failure information includes failed image information and failed review item information.

[0038] Specifically, after the CRC uploads the initial medical image sequence to the IRC system, the automated quality control program will review each medical image in the initial medical image sequence item by item based on all inspection items (for example, whether the medical image is complete and whether the medical image contains key areas required for the clinical trial project). If the quality control review fails (i.e., the quality control review fails), the IRC system sends a quality control review failure message to the research center, which includes information about the failed image and the failed review item.

[0039] After the research center uploads the supplementary medical images, considering that CRC errors may still occur during the supplementary upload stage, images of the subject's current examination that do not belong to the initial medical image sequence are uploaded to the IRC system. Therefore, it is necessary to determine M medical images to be reviewed that belong to the subject's current examination. The medical images to be reviewed are the examination images of the subject's current examination.

[0040] Step 102: Based on the M medical images to be reviewed and the failed image information, determine N incremental images corresponding to the subject.

[0041] Exemplarily, N is less than or equal to M.

[0042] Specifically, considering that there may be some images that have passed the quality control review (i.e., successful images) among the M medical images to be reviewed and that have been stored in the IRC system, based on the failed image information, the images that already exist in the IRC system among the M medical images to be reviewed are filtered out, and N incremental images corresponding to the subjects are obtained, so that only the incremental images are quality controlled, thereby reducing the system operating space occupancy rate.

[0043] Step 103: Based on the failed review item information, review the N incremental images to update the quality control results corresponding to the initial medical image sequence.

[0044] Specifically, based on the information about failed audit items, a specific review scanning procedure is developed to scan N incremental images, and each of the N incremental images is reviewed item by item. Since only incremental images are reviewed in a targeted manner, there is no need to review all audit items, effectively reducing system utilization.

[0045] In an embodiment of the present application, in response to the quality control review failure information of the initial medical image sequence corresponding to the subject, M medical images to be reviewed belonging to the subject's current examination are determined from the medical images supplemented by the CRC; based on the failed image information, images that already exist in the IRC system among the M medical images to be reviewed are filtered out to obtain N incremental images corresponding to the subject; based on the failed review item information, the N incremental images are reviewed in a targeted manner to update the quality control results corresponding to the initial medical image sequence. Through the above-mentioned medical image quality control method, the IRC system can perform efficient and targeted repeated quality control reviews on the medical images supplemented by the CRC, without the need for a full scan, effectively reducing system occupancy.

[0046] It should be noted that the failure to pass the review, unqualified review and unsuccessful review mentioned in this application are all expressions of quality control review failure.

[0047] Figure 2 FIG. 1 is a flow chart of a medical image quality control method provided by an embodiment of the present application. Figure 2 As shown, the step of determining M medical images to be reviewed corresponding to the subject includes the following steps.

[0048] Step 201: Based on the P supplementary medical images uploaded, determine the patient number information corresponding to each of the P supplementary medical images.

[0049] Exemplarily, P is greater than or equal to M. Then the quantity relationship among the supplementary medical images, the medical images to be reviewed, and the incremental images is P≥M≥N.

[0050] Specifically, when a medical image is taken, the medical image will carry information. The patient number information is the unique identifier of the patient. The patient number information can be used to identify the patient for whom the medical image was taken. Therefore, based on the patient number information corresponding to each of the P supplementary medical images, a basis is provided for subsequent judgment of whether the supplementary medical images belong to the subject.

[0051] It should be noted that the supplementary medical images in the embodiments of the present application are medical images supplemented by the research center in response to the information that the IRC system failed to review the quality control of the initial medical image sequence. The medical image to be reviewed is the medical image of the current examination of the current subject corresponding to the initial medical image sequence in the supplementary medical images. The incremental image is the newly added image corresponding to the failed image in the medical image to be reviewed, and does not include the successful image. In the embodiments of the present application, only the incremental image is reviewed, and in the prior art, the image obtained by merging the re-uploaded medical image with the original medical image is reviewed. The incremental image is different from the image obtained by merging the re-uploaded medical image with the original medical image.

[0052] For each of the P supplementary medical images, the following judgment process is performed to respectively judge whether the supplementary medical image is an examination image of the subject.

[0053] Step 202: Determine whether the patient number information corresponding to the supplementary medical image is the same as the subject number information corresponding to the subject.

[0054] Step 203: If not, delete the supplementary medical image and send the first feedback information to the research center.

[0055] Step 204: If yes, determine the examination number information corresponding to the supplementary medical image, and further determine whether the supplementary medical image is a medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence.

[0056] Specifically, a determination is made as to whether the patient number information corresponding to the supplementary medical image is identical to the subject number information corresponding to the subject. If the patient number information corresponding to the supplementary medical image is identical to the subject number information, the supplementary medical image is confirmed to belong to the examination image of the subject corresponding to the initial medical image sequence. For the supplementary medical image that has been determined to belong to the subject, its corresponding examination number information is further determined. Based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence, a determination is made as to whether the supplementary medical image belongs to the subject's current examination (i.e., the medical image to be reviewed). If the patient number information corresponding to the supplementary medical image is different from the subject number information, the image is determined not to belong to the subject's current examination, the image is deleted, and a first feedback message is sent to the research center.

[0057] Exemplarily, the first feedback message is used to indicate that the supplementary medical image uploaded by the research center does not belong to the subject and the CRC upload is incorrect.

[0058] In an embodiment of the present application, by determining whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence, it is determined whether the supplementary medical image belongs to the subject, and the supplementary medical image belonging to the subject is subsequently verified to obtain the medical image to be reviewed, so that the supplementary medical image that does not belong to the subject cannot be uploaded to the IRC system, thereby reducing the storage occupancy of the RC system and improving the system operation rate.

[0059] Figure 3 FIG. 1 is a flow chart of a medical image quality control method provided by an embodiment of the present application. Figure 3 As shown, the step of determining whether the supplementary medical image is a medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence includes the following steps.

[0060] Step 301: Determine whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence.

[0061] Specifically, the examination number information is a unique identifier of the examination, and the patient number information can be used to distinguish which examination of the subject it is, such as baseline visit examination, follow-up visit examination 1 or follow-up visit examination n.

[0062] Step 302: If yes, determine the supplementary medical image as the medical image to be reviewed.

[0063] Step 303: If not, determine the examination date information corresponding to the supplementary medical image.

[0064] Step 304: Based on the examination date information corresponding to the supplementary medical image and the examination date information corresponding to the initial medical image sequence, determine whether the supplementary medical image and the initial medical image sequence belong to the same examination window period.

[0065] Step 305: If they belong to the same examination window period, the supplementary medical image is determined as the medical image to be reviewed.

[0066] Step 306: If the images do not belong to the same examination window period, the supplementary medical image is deleted, and second feedback information is sent to the research center.

[0067] Specifically, determine whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence. If the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence, it represents that the images are generated by the same examination. It is determined that the supplementary medical image belongs to the image of the subject's current examination and is determined to be a medical image to be reviewed.

[0068] If the examination number information corresponding to the supplementary medical image is different from the examination number information corresponding to the initial medical image sequence, it cannot be directly determined that it does not belong to the subject's current examination. It is necessary to obtain the examination date information corresponding to the supplementary medical image, and based on the examination date information corresponding to the supplementary medical image and the examination date information corresponding to the initial medical image sequence, determine whether the supplementary medical image and the initial medical image sequence belong to the same examination window period. If they are in the same examination window period, it means that the supplementary medical image and the initial medical image sequence were examined in the same period, and the supplementary medical image also belongs to the subject's current examination image, that is, the medical image to be reviewed. If they are not in the same examination window period, it means that the supplementary medical image and the initial medical image sequence were not examined in the same period, and it is determined that the supplementary medical image belongs to the subject, but not to the subject's current examination, that is, it does not belong to the same examination as the initial medical image sequence, and it does not belong to the medical image to be reviewed. The image is deleted, and the second feedback information is sent to the research center.

[0069] Exemplarily, the second feedback message is used to indicate that the supplementary medical image uploaded by the research center does not belong to the current examination of the subject and that a CRC upload error occurs.

[0070] In an embodiment of the present application, by determining whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence, it is determined whether the supplementary medical image belongs to the current examination of the subject, so that the medical images to be reviewed that belong to the current examination of the subject are subject to subsequent review and quality inspection, and the supplementary medical images that do not belong to the current examination of the subject cannot be uploaded to the IRC system, thereby reducing the storage occupancy of the RC system and improving the system operation rate.

[0071] Through the above embodiment, M medical images to be reviewed belonging to the current examination of the subject are determined from the P supplementary uploaded images. Considering that the medical images to be reviewed should be new images uploaded for failed images that failed the quality control review, but due to CRC operation problems, successful images that have successfully passed the quality control review and are already stored in the IRC system may be packaged and uploaded together, based on the failed image information, the images that already exist in the IRC system among the M medical images to be reviewed are filtered out, and N incremental images corresponding to the subject are obtained, so that only the incremental images are quality controlled.

[0072] Figure 4FIG. 1 is a flow chart of a medical image quality control method provided by an embodiment of the present application. Figure 4 As shown, based on the M medical images to be reviewed and the failed image information, the step of determining the N incremental images corresponding to the subject includes the following steps.

[0073] Step 401: Determine image sequence identification information corresponding to each of M medical images to be reviewed.

[0074] Specifically, the image sequence identification information is a unique identifier of the image sequence. Exemplarily, the image sequence identification information may be an image sequence ID.

[0075] Determine the image sequence identification information corresponding to each of the M medical images to be reviewed, providing a basis for the subsequent determination of incremental images. Incremental images are newly added medical images belonging to the subject's current examination, compared to the successful images that passed quality control review in the initial medical image sequence.

[0076] For each of the M medical images to be reviewed, the following judgment process is performed to respectively determine whether each medical image to be reviewed is an incremental image.

[0077] Step 402: Determine whether the image sequence identification information corresponding to the medical image to be reviewed is the same as the image sequence identification information corresponding to the initial medical image sequence.

[0078] Step 403: Determine the medical image to be reviewed as an incremental image.

[0079] Step 404: If yes, determine the image identification information corresponding to the medical image to be reviewed, and further determine whether the medical image to be reviewed is an incremental image based on the image identification information corresponding to the medical image to be reviewed and the failed image information.

[0080] Specifically, the image identification information is a unique identifier of the image, and illustratively, the image identification information may be an image ID. The same image sequence includes multiple images, and accordingly, the same image sequence ID corresponds to multiple image IDs.

[0081] Determine whether the image sequence identification information corresponding to the medical image to be reviewed is the same as the image sequence identification information corresponding to the initial medical image sequence. If the image sequence identification information corresponding to the medical image to be reviewed is the same as the image sequence identification information corresponding to the initial medical image sequence, it indicates that an image in the image sequence corresponding to the image sequence identification already exists in the IRC system, but which image in the image sequence has been successfully uploaded for quality control review still needs further judgment. Therefore, it is necessary to further determine whether the medical image to be reviewed is an incremental image based on the image identification information corresponding to the medical image to be reviewed and the failed image information. If the image sequence identification information corresponding to the medical image to be reviewed is different from the image sequence identification information corresponding to the initial medical image sequence, it indicates that no image in the image sequence exists in the IRC system, that is, the medical image to be reviewed cannot exist in the system. Therefore, the medical image to be reviewed is determined to be an incremental image.

[0082] In an embodiment of the present application, by determining whether the image sequence identification information corresponding to the medical image to be reviewed is the same as the image sequence identification information corresponding to the initial medical image sequence, it is determined that the medical image to be reviewed corresponding to the image sequence identification information that does not exist at all in the system is an incremental image, and the medical image to be reviewed corresponding to the image sequence identification information that exists in the system is further identified to determine whether the medical image to be reviewed is an incremental image.

[0083] Figure 5 FIG. 1 is a flow chart of a medical image quality control method provided by an embodiment of the present application. Figure 5 As shown, further based on the image recognition information and failed image information corresponding to the medical image to be reviewed, determining whether the medical image to be reviewed is an incremental image step includes the following steps.

[0084] Step 501: Determine successful image information based on failed image information and an initial medical image sequence.

[0085] Specifically, when performing quality control review on the initial medical image sequence, failed image information and successful image information can be obtained, and the successful image information is the successful image that has passed the quality control review and is stored in the IRC system.

[0086] Step 502: Determine whether the image recognition information corresponding to the medical image to be reviewed is the same as the image recognition information corresponding to the successful image information.

[0087] Step 503: If yes, delete the medical image to be reviewed and send third feedback information to the research center.

[0088] Step 504: If not, determine the medical image to be reviewed as an incremental image.

[0089] Specifically, a determination is made as to whether the image identification information corresponding to the pending medical image is identical to the image identification information corresponding to the successful image information. If so, the pending medical image already exists in the IRC system, the pending medical image is deleted, and a third feedback message is sent. The third feedback message indicates that a supplementary medical image uploaded by the research center already exists in the IRC system and that a CRC upload error occurred. If the image identification information corresponding to the pending medical image is identical to the image identification information corresponding to the successful image information, the pending medical image does not exist in the IRC system, and the pending medical image is designated as an incremental image for subsequent quality control review.

[0090] In an embodiment of the present application, for medical images to be reviewed corresponding to image sequence identification information in the system, it is determined whether the image identification information corresponding to the medical image to be reviewed is the same as the image identification information corresponding to the successful image information, thereby determining whether the medical image to be reviewed is an incremental image, thereby filtering out the images that already exist in the IRC system among the M medical images to be reviewed, and then only performing quality control on the incremental images.

[0091] Figure 6 FIG. 1 is a flow chart of a medical image quality control method provided by an embodiment of the present application. Figure 6 As shown, based on the failed review item information, N incremental images are reviewed to update the quality control result steps corresponding to the initial medical image sequence, including the following steps.

[0092] Step 601: For each incremental image in the N incremental images, based on the failed audit item information, perform a quality control scan on the incremental image item by item to determine the scanning result of the incremental image.

[0093] Specifically, based on the information about failed audit items, a specific review scan procedure is developed for each incremental image. This means that only the failed items are reviewed to determine the scan results for the incremental image. This targeted scanning of incremental images eliminates the need for a full scan, effectively reducing system utilization.

[0094] Step 602: Based on the scanning results corresponding to each of the N incremental images, the quality control results corresponding to the initial medical image sequence are updated.

[0095] Specifically, based on the scanning results corresponding to each of the N incremental images, updating the quality control results corresponding to the initial medical image sequence includes the following two cases.

[0096] Case 1: When the scan results of all N incremental images are qualified, the quality control review failure information is deleted and the quality control result is updated to qualified. When the scan results of each of the N incremental images are qualified, the quality control review failure information is deleted, the quality control result of the initial medical image sequence is updated to qualified, and a qualified notification is sent to the CRC.

[0097] Case 2: When the scanning result of at least one of the N incremental images is unqualified, the quality control review failure information is updated based on the unqualified items in the scanning results of the N incremental images, and the quality control result is updated to failure; based on the updated quality control review failure information, the supplementary medical images uploaded again are quality controlled until the quality control result is qualified.

[0098] As long as the scanning result of one incremental image among the N incremental images is still unqualified, the updated quality control result corresponding to the initial medical image sequence is also still unqualified, that is, the repeated quality control review fails. Based on the unqualified items in the scanning results of the N incremental images, the quality control review failure information is updated and sent to the film reading center, so that the CRC can upload supplementary medical images again and repeat the steps in the above quality control method until the updated quality control result is qualified.

[0099] In this embodiment of the application, based on the failed review item information, a targeted repeat quality control review is performed on each incremental image, eliminating the need for a full scan and effectively reducing system occupancy. Updated quality control results are then sent to the quality control center, notifying them of the repeated quality control review pass or fail. This allows the CRC at the reading center to promptly perform subsequent operations based on the updated quality control results, improving work efficiency.

[0100] Exemplary medical image quality control device

[0101] Figure 7 The figure shows a schematic diagram of the structure of a medical image quality control device provided by an embodiment of the present application. The medical image quality control method provided by the embodiment of the present application is applied to a medical image reading system, and is used to perform quality control on medical images that are supplemented by the research center when the reading center fails to pass the review. Figure 7 As shown, the medical image quality control device 100 includes a first determination module 101 , a second determination module 102 and a third determination module 103 .

[0102] The first determination module 101 is configured to, in response to quality control review failure information for an initial medical image sequence corresponding to a subject, determine M medical images corresponding to the subject to be reviewed, wherein the quality control review failure information includes failed image information and failed review item information. The second determination module 102 is configured to determine N incremental images corresponding to the subject based on the M medical images to be reviewed and the failed image information. The third determination module 103 is configured to review the N incremental images based on the failed review item information to update the quality control results corresponding to the initial medical image sequence.

[0103] In an embodiment of the present application, the first determination module 101, in response to the quality control audit failure information of the initial medical image sequence corresponding to the subject, determines M medical images to be reviewed belonging to the current examination of the subject from the medical images supplemented by the CRC; the second determination module 102, based on the failed image information, filters out the images that already exist in the IRC system from the M medical images to be reviewed, and obtains N incremental images corresponding to the subject; the third determination module 103, based on the failed audit item information, repeats the quality control audit of the N incremental images in a targeted manner to update the quality control results corresponding to the initial medical image sequence. Through the above-mentioned medical image quality control method, the IRC system can efficiently and targetedly repeat the quality control audit of the medical images supplemented by the CRC, without the need for a full scan, effectively reducing the system occupancy rate.

[0104] Figure 8 FIG. 1 is a schematic diagram showing the structure of a first determination module in a medical image quality control device provided in one embodiment of the present application. Figure 8 As shown, the first determining module 101 further includes a first determining unit 1011 and a first judging unit 1012 .

[0105] The first determination unit 1011 is configured to, based on the P supplementary medical images that are uploaded, determine the patient number information corresponding to each of the P supplementary medical images. The first judgment unit 1012 is configured to, for each of the P supplementary medical images, determine whether the patient number information corresponding to the supplementary medical image is the same as the subject number information corresponding to the subject; if not, delete the supplementary medical image and send first feedback information to the research center; if so, determine the examination number information corresponding to the supplementary medical image, and further determine whether the supplementary medical image is a medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence.

[0106] In one embodiment, whether the supplementary medical image is a medical image to be reviewed is further determined based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence, including: judging whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence; if so, determining the supplementary medical image as a medical image to be reviewed; if not, determining the examination date information corresponding to the supplementary medical image, and based on the examination date information corresponding to the supplementary medical image and the examination date information corresponding to the initial medical image sequence, judging whether the supplementary medical image and the initial medical image sequence belong to the same examination window period; if they belong to the same examination window period, determining the supplementary medical image as a medical image to be reviewed; if they do not belong to the same examination window period, deleting the supplementary medical image, and sending second feedback information to the research center.

[0107] Figure 9 FIG. 1 is a schematic diagram showing the structure of a second determination module in a medical image quality control device according to an embodiment of the present application. Figure 9 As shown, the second determining module 102 includes: a second determining unit 1021 and a second judging unit 1022 .

[0108] The second determination unit 1021 is configured to determine the image sequence identification information corresponding to each of the M medical images to be reviewed; the second judgment unit 1022 is configured to determine, for each of the M medical images to be reviewed, whether the image sequence identification information corresponding to the medical image to be reviewed is the same as the image sequence identification information corresponding to the initial medical image sequence; if not, determine the medical image to be reviewed as an incremental image; if so, determine the image identification information corresponding to the medical image to be reviewed, and further determine whether the medical image to be reviewed is an incremental image based on the image identification information corresponding to the medical image to be reviewed and the failed image information.

[0109] In one embodiment, based on the image identification information corresponding to the medical image to be reviewed and the failed image information, determining whether the medical image to be reviewed is an incremental image includes: determining the successful image information based on the failed image information and the initial medical image sequence; judging whether the image identification information corresponding to the medical image to be reviewed is the same as the image identification information corresponding to the successful image information; if so, deleting the medical image to be reviewed and sending third feedback information to the research center; if not, determining the medical image to be reviewed as an incremental image.

[0110] Figure 10 FIG. 1 is a schematic diagram showing the structure of the third determination module in a medical image quality control device provided in one embodiment of the present application. Figure 10 As shown, the third determining module 103 further includes a third determining unit 1031 and an updating unit 1032 .

[0111] The third determination unit 1031 is configured to, for each incremental image in the N incremental images, perform a quality control scan on the incremental image item by item based on the failed audit item information to determine the scanning result of the incremental image; the updating unit 1032 is configured to update the quality control result corresponding to the initial medical image sequence based on the scanning results corresponding to each of the N incremental images.

[0112] In one embodiment, the third determination unit 1031 is further configured to, when the scanning results of N incremental images are all qualified, delete the quality control review failure information and update the quality control result to qualified; or, when the scanning result of at least one image among the N incremental images is unqualified, update the quality control review failure information based on the unqualified items in the scanning results of the N incremental images, and update the quality control result to failure; based on the updated quality control review failure information, perform quality control on the supplementary medical images uploaded again until the quality control result is qualified.

[0113] The specific functions and operations of the above-mentioned medical image quality control device have been referenced above. Figures 1 to 6 The medical image quality control method described in the figure is introduced in detail; the specific functions and operations of other modules in the medical image quality control device are introduced in detail. Figures 1 to 6 The medical image quality control method described in detail is described in detail, so its repeated description will be omitted here.

[0114] Exemplary electronic devices

[0115] Figure 11 The figure shows a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 11 As shown, electronic device 300 includes one or more processors 310 and memory 320 .

[0116] The processor 310 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 300 to perform desired functions.

[0117] The memory 320 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 310 may execute the program instructions to implement the medical image quality control methods of the various embodiments of the present application described above and / or other desired functions.

[0118] In one example, the electronic device 300 may further include an input device 330 and an output device 340 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0119] Of course, to simplify, Figure 11 Only some of the components related to the present application in the electronic device 300 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device 300 may further include any other appropriate components according to specific application scenarios.

[0120] Exemplary computer program products and computer-readable storage media

[0121] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the medical image quality control method provided according to various embodiments of the present application as described in the above-mentioned "Exemplary Magnetic Medical Image Quality Control Method" section of this specification.

[0122] The computer program product may be written in any combination of one or more programming languages ​​to implement the program code for performing the operations of the embodiments of the present application, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0123] In addition, an embodiment of the present application may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, causes the processor to execute the steps of the medical image quality control method provided according to the various embodiments of the present application described in the above-mentioned "Exemplary Medical Image Quality Control Method" section of this specification.

[0124] The computer-readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0125] It should be noted that the above examples are only specific embodiments of the present application. Obviously, the present application is not limited to the above examples, and many similar variations are possible. All variations directly derived or associated with the contents disclosed by those skilled in the art should fall within the scope of protection of the present application.

[0126] It should be understood that the first, second, etc. qualifiers mentioned in the embodiments of the present application are only used to more clearly describe the technical solutions of the embodiments of the present application and cannot be used to limit the scope of protection of the present application.

[0127] The above are only preferred embodiments of the present application and are not intended to limit the scope of protection of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A medical image quality control method, characterized in that: An automated quality control procedure for an independent central film reading system, the method comprising: In response to quality control review failure information of an initial medical image sequence corresponding to a subject, determining M medical images corresponding to the subject to be reviewed, wherein the quality control review failure information includes failed image information and failed review item information; Determining, based on the M medical images to be reviewed and the failed image information, N incremental images corresponding to the subject, where N is less than M, and the incremental images are newly added images in the medical images to be reviewed corresponding to the failed images and do not include successful images; Reviewing the N incremental images based on the failed review item information to update the quality control results corresponding to the initial medical image sequence; The determining of the M medical images to be reviewed corresponding to the subject includes: Based on the P supplementary medical images uploaded, respectively determine the patient number information corresponding to each of the P supplementary medical images; For each of the P supplementary medical images, determining whether the patient number information corresponding to the supplementary medical image is the same as the subject number information corresponding to the subject; If not, deleting the supplementary medical image and sending a first feedback message to the research center; If so, determining the examination number information corresponding to the supplementary medical image, and further determining whether the supplementary medical image is the medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence; The determining, based on the M medical images to be reviewed and the failed image information, N incremental images corresponding to the subject includes: Determining image sequence identification information corresponding to each of the M medical images to be reviewed; For each of the M medical images to be reviewed, determining whether image sequence identification information corresponding to the medical image to be reviewed is identical to image sequence identification information corresponding to the initial medical image sequence; If not, determining the medical image to be reviewed as the incremental image; If so, determine the image identification information corresponding to the medical image to be reviewed, and determine the successful image information based on the failed image information and the initial medical image sequence; judge whether the image identification information corresponding to the medical image to be reviewed is the same as the image identification information corresponding to the successful image information; if so, delete the medical image to be reviewed and send third feedback information to the research center; if not, determine the medical image to be reviewed as the incremental image.

2. The medical image quality control method according to claim 1, characterized in that: The further determining whether the supplementary medical image is the medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence includes: Determining whether the examination number information corresponding to the supplementary medical image is the same as the examination number information corresponding to the initial medical image sequence; If so, determining the supplementary medical image as the medical image to be reviewed; If not, determine the examination date information corresponding to the supplementary medical image, and based on the examination date information corresponding to the supplementary medical image and the examination date information corresponding to the initial medical image sequence, judge whether the supplementary medical image and the initial medical image sequence belong to the same examination window period; if they belong to the same examination window period, determine the supplementary medical image as the medical image to be reviewed; if they do not belong to the same examination window period, delete the supplementary medical image and send second feedback information to the research center.

3. The medical image quality control method according to any one of claims 1 to 2, characterized in that: The step of reviewing the N incremental images based on the failed review item information to update the quality control result corresponding to the initial medical image sequence includes: For each of the N incremental images, based on the failed audit item information, perform a quality control scan on the incremental image item by item to determine a scanning result of the incremental image; Based on the scanning results corresponding to each of the N incremental images, the quality control results corresponding to the initial medical image sequence are updated.

4. The medical image quality control method according to claim 3, characterized in that: The updating of the quality control results corresponding to the initial medical image sequence based on the scanning results corresponding to each of the N incremental images includes: When the scanning results of the N incremental images are all qualified, the quality control review failure information is deleted and the quality control result is updated to qualified; or When the scanning result of at least one of the N incremental images is unqualified, based on the unqualified items in the scanning results of the N incremental images, the quality control review failure information is updated, and the quality control result is updated to failure; Based on the updated quality control review failure information, quality control is performed on the supplementary medical images uploaded again until the quality control results are qualified.

5. A medical image quality control device, characterized in that: An automatic quality control program for an independent central film reading system, the device comprising: A first determining module is configured to determine M medical images corresponding to the subject to be reviewed in response to quality control review failure information of an initial medical image sequence corresponding to the subject, wherein the quality control review failure information includes failed image information and failed review item information; a second determining module configured to determine, based on the M medical images to be reviewed and the failed image information, N incremental images corresponding to the subject, where N is less than M, and the incremental images are newly added images in the medical images to be reviewed corresponding to the failed images and do not include successful images; a third determining module configured to review the N incremental images based on the failed review item information to update the quality control result corresponding to the initial medical image sequence; The first determining module is further configured to: Based on the P supplementary medical images uploaded, respectively determine the patient number information corresponding to each of the P supplementary medical images; For each of the P supplementary medical images, determining whether the patient number information corresponding to the supplementary medical image is the same as the subject number information corresponding to the subject; If not, deleting the supplementary medical image and sending a first feedback message to the research center; If so, determining the examination number information corresponding to the supplementary medical image, and further determining whether the supplementary medical image is the medical image to be reviewed based on the examination number information corresponding to the supplementary medical image and the examination number information corresponding to the initial medical image sequence; The second determining module is further configured to: Determining image sequence identification information corresponding to each of the M medical images to be reviewed; For each of the M medical images to be reviewed, determining whether image sequence identification information corresponding to the medical image to be reviewed is identical to image sequence identification information corresponding to the initial medical image sequence; If not, determining the medical image to be reviewed as the incremental image; If so, determine the image identification information corresponding to the medical image to be reviewed, and determine the successful image information based on the failed image information and the initial medical image sequence; judge whether the image identification information corresponding to the medical image to be reviewed is the same as the image identification information corresponding to the successful image information; if so, delete the medical image to be reviewed and send third feedback information to the research center; if not, determine the medical image to be reviewed as the incremental image.

6. An electronic device comprising: processor; as well as A memory, wherein computer program instructions are stored in the memory, and when the computer program instructions are executed by the processor, the processor is caused to execute the medical image quality control method according to any one of claims 1 to 4.

7. A computer-readable storage medium having computer program instructions stored thereon, wherein when the computer program instructions are executed by a processor, the processor is caused to execute the medical image quality control method according to any one of claims 1 to 4.

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