Medical image uploading method and device, electronic device and computer storage medium

Abstract

The present application provides a medical image uploading method, which is applied to a film reading system. The method includes: determining the basic image information corresponding to each of the P candidate medical image sets obtained from the research center; determining the basic project information corresponding to the preset clinical trial project in the film reading system; based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, the P candidate medical image sets are respectively filed into the visit items corresponding to each of the P candidate medical image sets. The medical image uploading method provided by the present application can achieve the purpose of uploading the image set to the corresponding visit item without manual operation by the user. Compared with the CRC manual image uploading method in the prior art, since there is no need for manual copying and manual uploading, it can not only improve the upload efficiency and the archiving efficiency of the image in the film reading system, but also reduce the rework caused by manual misoperation, thereby reducing labor costs and time costs.

Description

Technical Field

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

[0002] In the prior art, the Clinical Research Coordinator (CRC) of the research center needs to manually copy the examination images of each subject at each visit, and select or create the visit item name of the subject corresponding to the copied image in the Independent Review Center (IRC) system, and then complete the archiving separately.

[0003] However, manual copying and archiving require a lot of manpower and time costs, and the manual operation process is prone to deviations, which will bring heavy work to subsequent image inspections, further increasing manpower and time costs. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a medical image uploading method, a medical image uploading device, an electronic device and a computer-readable storage medium to solve the technical problems of high labor and time costs caused by the need for CRC to manually upload and archive images in the film reading system.

[0005] According to a first aspect of an embodiment of the present application, a medical image uploading method is provided, which is applied to a film reading system. The method includes: determining the basic image information corresponding to each of the P candidate medical image sets obtained from the research center; based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, filing the P candidate medical image sets into the visit items corresponding to each of the P candidate medical image sets.

[0006] In one embodiment, based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, the P candidate medical image sets are respectively filed into the visit items corresponding to each of the P candidate medical image sets, including: based on the basic image information corresponding to each of the P candidate medical image sets, determining the N subjects to which the P candidate medical image sets belong, so as to determine the M candidate medical image sets corresponding to each of the N subjects; for each of the N subjects, based on the basic image information and project basic information corresponding to each of the M candidate medical image sets, determining the subject matching items corresponding to the M candidate medical image sets; relationship; based on the basic image information and project basic information corresponding to each of the M candidate medical image sets, determine the subject matching relationship corresponding to the M candidate medical image sets; based on the subject matching relationship, the basic image information and project basic information corresponding to each of the M candidate medical image sets, determine the visit items corresponding to each of the M candidate medical image sets; based on the visit items corresponding to each of the M candidate medical image sets, respectively file the M candidate medical image sets into the visit items corresponding to each of the M candidate medical image sets, so as to respectively file the P candidate medical image sets into the visit items corresponding to each of the P candidate medical image sets.

[0007] In one embodiment, based on the basic image information and project basic information corresponding to each of the M candidate medical image sets, the subject matching relationship corresponding to the M candidate medical image sets is determined, including: based on the basic image information corresponding to each of the M candidate medical image sets, determining the subject information corresponding to the subjects to which the M candidate medical image sets belong; based on the project basic information, determining the subject information corresponding to each of the multiple subjects included in the clinical trial project; based on the subject information corresponding to the M candidate medical image sets and the subject information corresponding to each of the multiple subjects, determining the subject matching relationship.

[0008] In one embodiment, the subject matching relationship includes that multiple subjects included in the clinical trial project are not matched with the subjects to which the M candidate medical image sets belong, wherein based on the subject matching relationship, the basic image information and the project basic information corresponding to each of the M candidate medical image sets, the visit items corresponding to each of the M candidate medical image sets are determined, including: establishing the visit items corresponding to the subjects to which the M candidate medical image sets belong in the film reading system; determining the examination date information corresponding to each of the M candidate medical image sets based on the basic image information corresponding to each of the M candidate medical image sets; for the visit items, determining the visit items corresponding to each of the M candidate medical image sets based on the examination date information and the project basic information corresponding to each of the M candidate medical image sets.

[0009] In one embodiment, based on the examination date information and project basic information corresponding to each of the M candidate medical image sets, the visit items corresponding to each of the M candidate medical image sets are determined, including: based on the examination date information corresponding to each of the M candidate medical image sets, the examination sequence information corresponding to each of the M candidate medical image sets is determined; based on the examination sequence information, the earliest examination date is determined as the baseline visit time, and the visit item corresponding to the candidate medical image set corresponding to the earliest examination date is determined as the baseline visit item; based on the project basic information, the visit interval information and the visit window information are determined; based on the baseline visit time, the visit interval information and the visit window information, multiple follow-up visit items and the follow-up visit times corresponding to each of the multiple follow-up visit items are determined; based on the multiple follow-up visit items and the follow-up visit times corresponding to each of the multiple follow-up visit items, the follow-up visit items corresponding to each of the remaining candidate medical image sets in the M candidate medical image sets are determined.

[0010] In one embodiment, the subject matching relationship includes a subject included in the clinical trial project and a subject to which M candidate medical image sets belong, wherein based on the subject matching relationship, the basic image information corresponding to each of the M candidate medical image sets, and the project basic information, the visit items corresponding to each of the M candidate medical image sets are determined, including: determining the examination date information corresponding to each of the M candidate medical image sets; based on the project basic information, determining multiple follow-up visit items corresponding to the subjects matching the M candidate medical image sets, and the follow-up visit times corresponding to each of the multiple follow-up visit items; determining the follow-up visit items corresponding to each of the M candidate medical image sets based on the examination date information corresponding to each of the M candidate medical image sets and the follow-up visit times corresponding to each of the multiple follow-up visit items.

[0011] In one embodiment, after the P candidate medical image sets are respectively filed into the visit items corresponding to the P candidate medical images, the method further includes: updating the visit status information of the subject based on the filing results corresponding to the P candidate medical image sets; and presenting the updated visit status information.

[0012] In one embodiment, the method further includes: determining whether there is an abnormality in the visit status information; if so, sending a warning message to the research center.

[0013] In one embodiment, before the basic image information corresponding to each of the P candidate medical image sets in the image reading system, it also includes: for each medical image set in the multiple medical image sets received by the image reading system, determining whether the project identification information corresponding to the medical image set is the same as the project identification information corresponding to the preset clinical trial project in the image reading system, if not, deleting the medical image set; if so, determining the completeness detection result corresponding to the medical image set based on the basic image information corresponding to the medical image set, and determining whether the medical image set is a candidate medical image set based on the completeness detection result corresponding to the medical image set.

[0014] In one embodiment, based on the completeness detection result corresponding to the medical image set, determining whether the medical image set is a candidate medical image set includes: if the completeness detection result corresponding to the medical image set is qualified, determining the medical image set is a candidate medical image set; if the completeness detection result corresponding to the medical image set is unqualified, determining that the medical image set is not a candidate medical image set, and deleting the medical image set.

[0015] In one embodiment, based on the basic image information corresponding to the medical image set, determining the completeness detection result corresponding to the medical image set includes: determining the slice position information corresponding to each of the multiple medical image sequences included in the medical image set based on the basic image information corresponding to the medical image set; judging whether the anatomical position sequence corresponding to the multiple medical image sequences is correct based on the slice position information corresponding to each of the multiple medical image sequences; if not, determining that the completeness detection result is unqualified; if so, determining the sequence continuity information corresponding to each of the multiple medical image sequences based on the basic image information corresponding to the medical image set to further determine the completeness detection result corresponding to the medical image set.

[0016] In one embodiment, based on basic image information corresponding to a medical image set, sequence continuity information corresponding to each of a plurality of medical image sequences is determined to further determine an integrity detection result corresponding to the medical image set, including: for each medical image sequence in a plurality of medical image sequences, encoding information corresponding to each of a plurality of medical images included in the medical image sequence is determined; based on the encoding information corresponding to the plurality of medical images, whether the encodings corresponding to the plurality of medical images are continuous is judged to determine the sequence continuity information; if the sequence continuity information corresponding to each of the plurality of medical image sequences is qualified, the integrity detection result corresponding to the medical image set is qualified; if the sequence continuity information corresponding to one of the plurality of medical image sequences is unqualified, the integrity detection result corresponding to the medical image set is unqualified.

[0017] According to a second aspect of an embodiment of the present application, a medical image uploading device is provided, which is applied to a film reading system, and the device includes: a first determination module, configured to determine the basic image information corresponding to each of P candidate medical image sets in the film reading system; a second determination module, configured to determine the basic project information corresponding to a preset clinical trial project in the film reading system; and an archiving module, configured to archive the P candidate medical image sets into the visit items corresponding to each of the P candidate medical image sets based on the basic image information and project basic information corresponding to each of the P candidate medical image sets.

[0018] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: a processor; and a memory, in which computer program instructions are stored, and when the computer program instructions are executed by the processor, the processor executes the medical image uploading method as described in the first aspect above.

[0019] 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 uploading method as described in the first aspect above.

[0020] The medical image uploading method provided in the embodiment of the present application is applied to a medical image reading system. The medical image uploading method, after the reading system synchronously receives the medical images collected by the image acquisition device in the research center, first determines the basic image information corresponding to each of the P candidate medical image sets in the reading system, then determines the basic project information corresponding to the preset clinical trial project in the reading system, and finally, based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, archives the P candidate medical image sets to the visit items corresponding to each of the P candidate medical image sets, thereby realizing an image uploading process without manual operation. Compared with the CRC manual image uploading method in the prior art, since there is no need for manual copying and manual uploading, it can not only improve the uploading efficiency and the archiving efficiency of the image in the reading system, but also reduce the rework caused by manual misoperation, thereby reducing labor costs and time costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0022] Figure 2 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0023] Figure 3 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0024] Figure 4The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0025] Figure 5 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0026] Figure 6 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0027] Figure 7 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0028] Figure 8 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0029] Fig. 9 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0030] Fig.10 The figure is a flow chart of a medical image uploading method provided in one embodiment of the present application.

[0031] Fig.11 Shown is a schematic diagram of the structure of a medical image uploading device provided in one embodiment of the present application.

[0032] Fig.12 Shown is a schematic diagram of the structure of an archiving module provided in an embodiment of the present application.

[0033] Fig.13 Shown is a schematic diagram of the structure of a subject matching unit provided in one embodiment of the present application.

[0034] Fig.14 Shown is a schematic diagram of the structure of a medical image uploading device provided in one embodiment of the present application.

[0035] Fig.15 Shown is a schematic diagram of the structure of a medical image uploading device provided in one embodiment of the present application.

[0036] Fig.16 Shown is a schematic diagram of the structure of a second execution module provided in an embodiment of the present application.

[0037] Fig.17 Shown is a schematic diagram of the structure of a second execution module provided in an embodiment of the present application.

[0038] Fig.18 Shown is a schematic structural diagram of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0040] 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, independent readers need to measure and annotate lesions on medical images, and medical images come from the image acquisition equipment of the imaging department of each research center. Therefore, the research center needs to upload medical images to the IRC system for independent readers to retrieve for reading.

[0041] In the prior art, CRC needs to manually copy the medical images in the image acquisition device to the disk, and manually upload the medical images in the disk to the IRC system through a computer. Specifically, CRC manually copies each visit examination image of each subject, and selects or creates the follow-up visit name of the subject corresponding to the copied image in the IRC system, and then archives them separately.

[0042] However, manual copying and archiving require a lot of manpower and time costs, and the manual operation process is prone to deviations, which will bring heavy work to subsequent image inspections, further increasing manpower and time costs.

[0043] In order to solve the above problems, the embodiment of the present application provides a medical image uploading method to realize the image uploading process without manual operation. Compared with the CRC manual image uploading method in the prior art, the medical image uploading method can improve the uploading efficiency and the archiving efficiency of the image in the film reading system, and reduce the rework caused by manual misoperation, thereby reducing the labor cost and time cost.

[0044] Combine the following Figures 1 to 13 The medical image uploading method, medical uploading quality control device, electronic device and computer-readable storage medium mentioned in the embodiments of the present application are introduced in detail.

[0045] Exemplary medical image upload method

[0046] Figure 1The figure shows a flow chart of a medical image uploading method provided in an embodiment of the present application. The medical image uploading method provided in an embodiment of the present application is applied to a film reading system (i.e., an IRC system) to upload a candidate medical image set corresponding to a visit examination of a subject collected by a research and development center to the visit item of the subject matching the candidate image in the IRC system.

[0047] Specifically, the medical images collected by the image acquisition equipment of the research center are automatically and synchronously transmitted to the IRC system. The IRC system first receives all the medical images and then executes the steps in the following medical image uploading method to complete the uploading of the medical images.

[0048] like Figure 1 As shown, the medical image uploading method includes the following steps.

[0049] Step 101: Determine basic image information corresponding to each of P candidate medical image sets obtained from the research center.

[0050] Exemplarily, P candidate medical image sets belong to N subjects of a clinical trial project, P is a positive integer greater than or equal to 1, and N is a positive integer greater than or equal to 1 and less than or equal to P.

[0051] Specifically, in a clinical trial project, after the subject is treated with drugs and / or medical devices, the subject will be regularly visited and examined, and medical images of the visits and examinations will be collected. The medical images of each visit and examination form a medical image set. The research center automatically and synchronously transmits the collected multiple medical image sets to the IRC system. For the received medical image set, it is determined that the collected medical image set belongs to the clinical trial project according to the project number corresponding to the received medical image set, and the completeness detection is performed based on the basic image information corresponding to the medical image set, so as to obtain a candidate medical image set. For the candidate medical image set, the collected medical images need to be archived in the IRC system in the corresponding clinical trial project. Among them, after the IRC system receives all the medical image sets, the received medical image sets are determined as candidate medical images after monitoring, and the specific process of determining the medical image set as a candidate medical image set will be explained in the subsequent embodiments.

[0052] Each candidate medical image set in the IRC system is a set of medical images of each visit and examination of the subject. By parsing the candidate medical image set, the basic image information corresponding to each of the P candidate medical image sets is determined. The basic image information corresponding to the candidate medical image set is the basic parameter information of the candidate medical image set. The basic image information corresponding to the candidate medical image set includes subject information and examination date information.

[0053] Step 102: Determine the basic project information corresponding to the preset clinical trial project in the film reading system.

[0054] Specifically, the project manager will preset the basic project information corresponding to the clinical trial project in the IRC system in advance. The basic project information is the basic parameter information of the preset clinical trial project. The basic project information includes: subject information corresponding to multiple subjects in the project, multiple visit items corresponding to each subject, etc., wherein the visit item is used to characterize the stage of the visit examination conducted by the subject.

[0055] Step 103: Based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, the P candidate medical image sets are respectively filed into the visit items corresponding to each of the P candidate medical image sets.

[0056] Specifically, for each candidate medical image set in the P candidate medical image sets, the image basic information and project basic information corresponding to the candidate medical image set are matched to determine the visit item corresponding to the candidate medical image set, so that each candidate medical image set in the P candidate medical image sets is respectively filed into the corresponding visit item.

[0057] In the embodiment of the present application, the basic image information corresponding to each of the P candidate medical image sets in the film reading system is first determined, and then the basic project information corresponding to the preset clinical trial project in the film reading system is determined. Finally, based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, the P candidate medical image sets are respectively filed into the visit items corresponding to each of the P candidate medical image sets, thereby realizing the image upload process without manual operation. Compared with the CRC manual image upload method in the prior art, since there is no need for manual copying and manual filing, it can not only improve the upload efficiency and the filing efficiency of the image in the film reading system, but also reduce the rework caused by manual misoperation, thereby reducing the labor cost and time cost.

[0058] It should be noted that the implementation entity of the medical image uploading method provided in the embodiment of the present application is the core processor of the IRC system.

[0059] Figure 2 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Figure 2 As shown, based on the basic image information and project basic information corresponding to each of the P candidate medical image sets, the steps of respectively filing the P candidate medical image sets into the visit items corresponding to each of the P candidate medical image sets include the following steps.

[0060] Step 201: Based on basic image information corresponding to each of the P candidate medical image sets, determine N subjects to which the P candidate medical image sets belong, so as to determine M candidate medical image sets corresponding to each of the N subjects.

[0061] Specifically, the P candidate medical image sets received by the IRC system may belong to N subjects. According to the basic image information corresponding to each candidate medical image set in the P candidate medical image sets, the subject to which each candidate medical image set belongs is determined, thereby obtaining the N subjects to which the P candidate medical image sets belong, that is, determining the M candidate medical image sets corresponding to each subject in the N subjects. Wherein, M is a positive integer greater than or equal to 1, and P is equal to M multiplied by N.

[0062] Step 202: for each of the N subjects, based on the basic image information and project basic information corresponding to each of the M candidate medical image sets, determine the subject matching relationship corresponding to the M candidate medical image sets.

[0063] Specifically, for each of the N subjects to which the P candidate medical image sets belong, the M candidate medical image sets corresponding to each of the N subjects are respectively filed into the corresponding method items, so that the P candidate medical image sets can be respectively filed into the visit items corresponding to the P candidate medical image sets.

[0064] For the M candidate medical image sets corresponding to each subject among the N subjects, considering that the M candidate medical image sets belong to the same subject, by matching the image basic information and the project basic information, the subject matching relationship corresponding to the M candidate medical image sets can be determined, that is, it can be determined whether there are subjects among the multiple subjects included in the clinical trial project that match the subjects to which the M candidate medical image sets belong, thereby providing a basis for subsequent archiving.

[0065] Step 203: Based on the subject matching relationship, the basic image information and the basic project information corresponding to each of the M candidate medical image sets, determine the visit items corresponding to each of the M candidate medical image sets.

[0066] Specifically, after determining the subject matching relationship, based on the subject matching relationship, the visit items corresponding to each of the M candidate medical image sets are further determined according to the image basic information and item basic information corresponding to each of the M candidate medical image sets.

[0067] Step 204: Based on the visit items corresponding to each of the M candidate medical image sets, the M candidate medical image sets are respectively filed into the visit items corresponding to each of the M candidate medical image sets, so as to respectively file the P candidate medical image sets into the visit items corresponding to each of the P candidate medical image sets.

[0068] Specifically, after determining the visit item corresponding to each of the M candidate medical image sets, each candidate medical image set is archived into its corresponding visit item, so that the M candidate medical image sets are respectively archived into the visit items corresponding to the M candidate medical images, and then the P candidate medical image sets are respectively archived into the visit items corresponding to the P candidate medical image sets.

[0069] In an embodiment of the present application, first, based on the basic image information corresponding to each of the P candidate medical image sets, N subjects to which the P candidate medical image sets belong are determined, and then, for each of the N subjects to which the P candidate medical image sets belong, based on the basic image information and project basic information corresponding to each of the M candidate medical image sets, the subject matching relationship corresponding to the M candidate medical image sets is determined, and then, based on the subject matching relationship, the basic image information and project basic information corresponding to each of the M candidate medical image sets, the visit items corresponding to each of the M candidate medical image sets are determined, and finally, based on the visit items corresponding to each of the M candidate medical image sets, the M candidate medical image sets are respectively archived in the visit items corresponding to each of the M candidate medical images, thereby realizing the archiving of the P candidate medical images belonging to the N subjects.

[0070] Figure 3 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Figure 3 As shown, based on the basic image information and project basic information corresponding to each of the M candidate medical image sets, the step of determining the subject matching relationship corresponding to the M candidate medical image sets includes the following steps.

[0071] Step 301: Based on basic image information corresponding to each of the M candidate medical image sets, determine subject information corresponding to the subject to which the M candidate medical image sets belong.

[0072] Specifically, the subject information is the unique identifier of the subject, and the subject information can be used to identify the subject information for which the medical image was taken. By parsing the basic image information corresponding to each of the M candidate medical image sets, the subject information corresponding to the subject to which the M candidate medical image sets belong is obtained.

[0073] Step 302: Based on the basic project information, determine the subject information corresponding to each of the multiple subjects included in the clinical trial project.

[0074] Specifically, each clinical trial project includes multiple subjects, and each subject has corresponding subject information.

[0075] Step 303: Determine a subject matching relationship based on the subject information corresponding to the M candidate medical image sets and the subject information corresponding to each of the multiple subjects.

[0076] Specifically, by matching the subject information corresponding to the M candidate medical image sets with the subject information corresponding to each of the multiple subjects, it is determined whether there are subjects among the multiple subjects included in the clinical trial project that match the subjects to which the M candidate medical image sets belong.

[0077] In an embodiment of the present application, based on the basic information of the project, the subject information corresponding to each of the multiple subjects included in the clinical trial project is determined, and based on the subject information corresponding to the M candidate medical image sets and the subject information corresponding to each of the multiple subjects, it is determined whether there are subjects among the multiple subjects included in the clinical trial project that match the subjects to which the M candidate medical image sets belong, thereby providing a basis for subsequent archiving.

[0078] Considering that the matching relationship of subjects includes two situations: (1) multiple subjects included in the clinical trial project do not match the subjects to which the M candidate medical image sets belong; (2) the subject matching relationship includes that a subject included in the clinical trial project matches the subjects to which the M candidate medical image sets belong. For the above two situations, based on the subject matching relationship, the basic image information and project basic information corresponding to each of the M candidate medical image sets, determining the visit items corresponding to each of the M candidate medical image sets also includes the following two situations.

[0079] In one embodiment, when the subject matching relationship is that the multiple subjects included in the clinical trial project do not match the subjects to which the M candidate medical image sets belong, such as Figure 4 As shown ( Figure 4 The figure shows a flow chart of a medical image uploading method provided in one embodiment of the present application, wherein the steps of determining the visit items corresponding to each of the M candidate medical image sets are based on the subject matching relationship, the basic image information and the basic project information corresponding to each of the M candidate medical image sets, and include the following steps.

[0080] Step 401: Establish multiple visit items corresponding to the subjects to which the M candidate medical image sets belong in the image reading system.

[0081] Specifically, considering that there are no subjects in the IRC system that match the subjects corresponding to the M candidate medical image sets, it is necessary to automatically establish multiple visit items corresponding to the subjects to which the M candidate medical image sets belong in the clinical trial project in the IRC system so that the M candidate medical image sets can be matched and archived.

[0082] Step 402: Based on the basic image information corresponding to each of the M candidate medical image sets, determine the examination date information corresponding to each of the M candidate medical image sets.

[0083] Specifically, the basic image information includes examination date information. By analyzing the basic image information corresponding to each of the M candidate medical image sets, the examination date information corresponding to each of the M candidate medical image sets can be determined.

[0084] The examination date information is the date on which the candidate image information is obtained (i.e., the date of the visit examination). Since the M candidate medical image sets are collected from M visit examinations, the M candidate medical image sets each correspond to different examination date information. The format of the examination date information includes "year, month, day".

[0085] Step 403: For the multiple established visit items, based on the examination date information and project basic information corresponding to each of the M candidate medical image sets, determine the visit item corresponding to each of the M candidate medical image sets.

[0086] Specifically, after establishing multiple visit items corresponding to the subjects to which the M candidate medical image sets belong in the IRC system, based on the examination date information and project basic information corresponding to each of the M candidate medical image sets, determine which established visit item of the subject each of the M candidate medical image sets corresponds to, that is, determine the visit item to which each of the M candidate medical image sets corresponds, thereby further providing a basis for subsequent archiving.

[0087] In an embodiment of the present application, in the case where there are no subjects in the IRC system that match the subjects corresponding to the M candidate medical image sets, first, multiple visit items corresponding to the subjects are established in the IRC system, and then based on the basic image information corresponding to each of the M candidate medical image sets, the examination date information corresponding to each of the M candidate medical image sets is determined, and finally, for the multiple established visit items, based on the examination date information and project basic information corresponding to each of the M candidate medical image sets, the visit item corresponding to each of the M candidate medical image sets is determined, thereby achieving the purpose of providing a further basis for subsequent archiving.

[0088] Figure 5 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Figure 5 As shown, based on the examination date information and project basic information corresponding to each of the M candidate medical image sets, the step of determining the visit item corresponding to each of the M candidate medical image sets includes the following steps.

[0089] Step 501: Based on the examination date information corresponding to each of the M candidate medical image sets, determine the examination sequence information corresponding to the M candidate medical image sets.

[0090] Specifically, based on the examination date information corresponding to each of the M candidate medical image sets, the examination sequence information corresponding to the M candidate medical image sets is determined, providing a basis for subsequently determining the visit items corresponding to each of the M candidate medical image sets.

[0091] Step 502: Based on the examination sequence information, the earliest examination date is determined as the baseline visit time, and the visit item corresponding to the candidate medical image set corresponding to the earliest examination date is determined as the baseline visit item.

[0092] Specifically, the earliest examination time is determined as the baseline visit time corresponding to the baseline visit item, and a corresponding relationship between the candidate medical image set with the earliest examination time and the baseline visit item of the subject is established, that is, the visit item corresponding to the candidate medical image set with the earliest examination time is the baseline visit item.

[0093] Step 503: Based on the basic information of the project, determine the visit interval information and the visit window information.

[0094] Step 504: Based on the baseline visit time, the visit interval information, and the visit window information, determine a plurality of follow-up visit items and the follow-up visit times corresponding to the plurality of follow-up visit items.

[0095] Specifically, based on the system preset visit interval information and visit window information and the baseline visit time, the follow-up visit times corresponding to multiple follow-up visit items are obtained through calculation.

[0096] For example, the earliest examination date in the M candidate medical image sets is 2020-01-01, and the baseline visit time is 2020-01-01. The IRC preset visit interval days are 30 days, the window days are ±2 days, and the follow-up visit time of follow-up visit item 1 is from 2020-01-28 to 2020-02-01, and so on, to determine the follow-up visit time corresponding to each of the multiple follow-up visit items.

[0097] Step 505: Based on the multiple follow-up visit items and the follow-up visit times corresponding to the multiple follow-up visit items, determine the follow-up visit items corresponding to the remaining candidate medical image sets in the M candidate medical image sets.

[0098] Specifically, for the M candidate medical image sets, excluding the candidate medical image set with the earliest examination time, the remaining M-1 candidate medical image sets are determined by matching the examination date information corresponding to each of the remaining M-1 candidate medical image sets with the follow-up visit times corresponding to each of the multiple follow-up visit items.

[0099] For example, continuing with the above example, based on the examination order information, the examination date information of the second ranked candidate medical image set is matched with the follow-up visit time of follow-up visit item 1 to determine that the visit item corresponding to the second ranked candidate medical image set is follow-up visit item 1. If the examination date of the second ranked candidate medical image set is between 2020-01-28 and 2020-02-01, the visit item corresponding to the second ranked candidate medical image set is determined to be follow-up visit item 1.

[0100] In an embodiment of the present application, for subjects in the IRC system who do not match the subjects corresponding to the M candidate medical image sets, after automatically establishing multiple visit items corresponding to the subjects in the IRC system, the above steps are used to determine the visit items corresponding to the M candidate medical image sets, respectively, to provide a basis for the subsequent archiving of the M candidate medical image sets.

[0101] In another embodiment, when the subject matching relationship includes a subject included in the clinical trial project and a subject to which the M candidate medical image sets belong, such as Figure 6 As shown ( Figure 6 The figure shows a flow chart of a medical image uploading method provided in one embodiment of the present application, wherein the steps of determining the visit items corresponding to each of the M candidate medical image sets are based on the subject matching relationship, the basic image information and the basic project information corresponding to each of the M candidate medical image sets, and include the following steps.

[0102] Step 601: Determine the examination date information corresponding to each of the M candidate medical image sets.

[0103] Specifically, considering that there is a subject in the IRC system that matches the subjects corresponding to the M candidate medical image sets, that is, this is not the first time that the subject has uploaded the examination images. There is no need to establish the visit items of the subject in the IRC system. It is only necessary to directly determine the correspondence between the M candidate medical image sets and the multiple visit items corresponding to the matching subject.

[0104] First, the examination date information corresponding to each of the M candidate medical image sets is obtained for subsequent matching.

[0105] Step 602: Based on the basic project information, determine a plurality of follow-up visit items corresponding to the subjects matching the M candidate medical image sets, and a follow-up visit time corresponding to each of the plurality of follow-up visit items.

[0106] Specifically, since there are subjects in the IRC system that match the subjects corresponding to the M candidate medical image sets, the follow-up visit times corresponding to the multiple follow-up visit items corresponding to the matched subjects are obtained according to the basic information of the items preset by the IRC system.

[0107] Step 603: Determine the follow-up visit items corresponding to each of the M candidate medical image sets based on the examination date information corresponding to each of the M candidate medical image sets and the follow-up visit times corresponding to each of the multiple follow-up visit items.

[0108] Specifically, by matching the examination date information corresponding to each of the M candidate medical image sets and the follow-up visit times corresponding to each of the multiple follow-up visit items, the follow-up visit items corresponding to each of the M candidate medical image sets are determined.

[0109] In an embodiment of the present application, through the above steps, the follow-up visit items corresponding to the M candidate medical image sets are directly determined, which provides for the subsequent archiving of the M candidate medical image sets.

[0110] Figure 7 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Figure 7 As shown, after the step of respectively filing the P candidate medical image sets into the visit items corresponding to the P candidate medical images, the image uploading method further includes the following steps.

[0111] Step 701: Update the visit status information of the subject based on the archiving results corresponding to each of the P candidate medical image sets.

[0112] Step 702: Present updated visit status information.

[0113] Specifically, according to the archiving results corresponding to each of the P candidate medical image sets, the visit status information corresponding to each of the multiple visit items corresponding to the multiple subjects in the IRC system is determined, and the follow-up visit information is displayed on a panel so that the operating personnel of the research center and IRC can check the status of the candidate images at any time.

[0114] In one embodiment, the medical image uploading method further includes: determining whether there is any abnormality in the visit status information; if so, sending a warning message to the research center.

[0115] Specifically, when the follow-up visit status information is abnormal, that is, a subject has not been examined during the window period, a warning message will be sent to the CRC so that the CRC can urge the subject to be examined.

[0116] The IRC system synchronously receives multiple medical image sets sent by the research center, but some of the medical image sets may not belong to the preset clinical trial project. Therefore, it is necessary to delete the medical image sets that do not belong to the preset clinical trial project. At the same time, considering the incompleteness of the medical image set itself due to the failure of the acquisition equipment or improper operation, the integrity of the medical image set is tested. When it is determined that the medical image set belongs to the preset clinical trial project and the integrity test result is qualified, the medical image set is determined as a candidate medical image.

[0117] Specifically, Figure 8 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Figure 8 As shown, after the step of determining the basic image information corresponding to each of the P candidate medical image sets in the image reading system, the image uploading method further includes the following steps.

[0118] Step 801: for each medical image set among a plurality of medical image sets received by an image reading system, determining whether the project identification information corresponding to the medical image set is the same as the project identification information corresponding to a preset clinical trial project in the image reading system.

[0119] Step 802: If yes, delete the medical image set.

[0120] Step 803: If not, determine the completeness detection result corresponding to the medical image set based on the basic image information corresponding to the medical image set, and determine whether the medical image set is a candidate medical image set based on the completeness detection result corresponding to the medical image set.

[0121] Specifically, for each medical image set among the multiple medical image sets received by the film reading system, the project identification information corresponding to the medical image set is determined based on the basic image information corresponding to the medical image set, and it is judged whether the project identification information corresponding to the medical image set is the same as the project identification information corresponding to the preset clinical trial project.

[0122] If the project identification information corresponding to the medical image set is different from the project identification information corresponding to the preset clinical trial project, the medical image set does not belong to the preset clinical trial project and the medical image set is deleted. If the project identification information corresponding to the medical image set is the same as the project identification information corresponding to the preset clinical trial project, the medical image set belongs to the preset clinical trial project, but its completeness still needs to be tested to determine whether the medical image set is a candidate medical image set.

[0123] Exemplarily, the project identification information may be a project number.

[0124] In an embodiment of the present application, the medical image set belonging to the preset clinical trial project is checked for completeness by determining whether the project identification information corresponding to the medical image set is identical to the project identification information corresponding to the preset clinical trial project to obtain a candidate medical image set, and the medical image set that does not belong to the preset clinical trial project is removed from the IRC system, thereby reducing the amount of ineffective work done by the IRC in subsequent archiving and improving archiving efficiency.

[0125] In a further embodiment, Figure 8 As shown, based on the completeness detection result corresponding to the medical image set, the step of determining whether the medical image set is a candidate medical image set includes:

[0126] Step 804: If the integrity detection result corresponding to the medical image set is qualified, the medical image set is determined to be a candidate medical image set.

[0127] Step 805: If the integrity detection result corresponding to the medical image set is unqualified, it is determined that the medical image set is not a candidate medical image set, and the medical image set is deleted.

[0128] Specifically, when a medical image set belongs to a preset clinical project, the medical image set is tested for completeness based on the basic information of the images corresponding to the medical image set, and the completeness test result corresponding to the medical image set is determined. When the completeness test result corresponding to the medical image set is qualified, the medical image belongs to the preset clinical project and there is no completeness problem. The medical image set is determined to be a candidate medical image set for subsequent archiving and upload. When the completeness test result corresponding to the medical image set is unqualified, although the medical image belongs to the preset clinical project, there is a completeness problem. The medical image set does not belong to the candidate medical image set and does not need to be subsequently archived. It is directly deleted to reduce the occupancy rate of the IRC system.

[0129] Fig. 9 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Fig. 9 As shown, based on the basic image information corresponding to the medical image set, the step of determining the completeness detection result corresponding to the medical image set includes the following steps.

[0130] Step 901: Based on basic image information corresponding to a medical image set, slice position information corresponding to each of a plurality of medical image sequences included in the medical image set is determined.

[0131] Step 902: Based on the slice position information corresponding to each of the multiple medical image sequences, determine whether the anatomical position sequence corresponding to the multiple medical image sequences is correct.

[0132] Step 903: If not, determine that the integrity test result is unqualified.

[0133] Step 904: If yes, determine the sequence continuity information corresponding to each of the plurality of medical image sequences based on the basic image information corresponding to the medical image set, so as to further determine the integrity detection result corresponding to the medical image set.

[0134] Specifically, the medical image set is a medical image of a follow-up examination of a subject, and the medical image set includes multiple medical image sequences. For the medical image sequence, the slice position information corresponding to each medical image sequence is used to characterize the relative position of the organ in the anatomy. Since the anatomical position order corresponding to multiple medical image sequences in the same medical image set should follow a preset rule, the completeness of the medical image set at the orientation level is judged by the anatomical position order corresponding to the multiple medical image sequences.

[0135] If the anatomical position order corresponding to multiple medical image sequences in the same medical image set does not meet the preset rules, it indicates that the anatomical position order corresponding to the multiple medical image sequences is incorrect, the detection result corresponding to the medical image set is judged to be unqualified, the medical image set is not a candidate medical image set, and the medical image set is deleted from the IRC system.

[0136] If the anatomical position sequence corresponding to multiple medical image sequences in the same medical image set follows the preset rule, indicating that the anatomical position sequence corresponding to the multiple medical image sequences is correct, then the detection result corresponding to the medical image set is judged to be qualified, thereby indicating that the integrity detection of the medical image set at the sequence orientation level is qualified. Although the integrity of the medical image set at the sequence orientation level is qualified, the continuity of multiple images in the sequence still needs to be detected to determine whether there are missing pages in the medical image sequence in the medical image set, so as to further determine the integrity detection result corresponding to the medical image set.

[0137] Exemplarily, the slice location information may be a slice location code (Slice Location Number). If the Slice Location Numbers corresponding to multiple medical image sequences in a medical image set satisfy the order from small to large or from large to small, then the medical image set is determined to have passed the integrity test at the sequence orientation level.

[0138] In an embodiment of the present application, based on slice position information corresponding to each of a plurality of medical image sequences, it is determined whether the anatomical position order corresponding to the plurality of medical image sequences is correct; for a medical image set with an incorrect anatomical position order, its integrity test result is determined to be unqualified, and the medical image set is deleted to reduce the burden for subsequent archiving; a sequence continuity test is performed on each of the plurality of medical image sequences in the medical image set with a correct anatomical position order to further determine the integrity test result corresponding to the medical image set, thereby obtaining a candidate image set for archiving.

[0139] Fig.10 FIG. 1 is a flow chart of a medical image uploading method provided by an embodiment of the present application. Fig.10 As shown, based on the basic image information corresponding to the medical image set, the sequence continuity information corresponding to each of the multiple medical image sequences is determined to further determine the completeness detection result step corresponding to the medical image set, including the following steps.

[0140] Step 1001: for each medical image sequence among a plurality of medical image sequences, determine the encoding information corresponding to each of the plurality of medical images included in the medical image sequence.

[0141] Step 1002: Based on the coding information corresponding to the multiple medical images, determine whether the codes corresponding to the multiple medical images are continuous to determine sequence continuity information.

[0142] Specifically, a medical image set includes multiple medical image sequences, and a medical image sequence includes multiple medical images. Based on the basic image information corresponding to the entire medical image set, the encoding information corresponding to each of the multiple medical images in each of the multiple medical image sequences in the medical image set is determined.

[0143] For each medical image sequence in the multiple medical image sequences, it is determined whether the codes corresponding to the multiple medical images are continuous according to the coding information corresponding to the multiple medical images, and whether the medical image sequence is missing a page, thereby determining the sequence continuity information. If the codes corresponding to the multiple medical images are continuous, the medical image sequence is not missing a page, and the sequence continuity information corresponding to the medical image sequence is qualified; if the codes corresponding to the multiple medical images are discontinuous, the medical image sequence is missing a page, and the sequence continuity information corresponding to the medical image sequence is unqualified.

[0144] Exemplarily, the coding information is an image code (Instance Number). If the Instance Numbers of the same sequence are continuous, it indicates that the medical image sequence has no missing pages. If the Instance Numbers of the same sequence are discontinuous, it indicates that the medical image sequence has missing pages.

[0145] Step 1003: If the sequence continuity information corresponding to each of the plurality of medical image sequences is qualified, the integrity detection result corresponding to the medical image set is qualified.

[0146] Step 1004: If the sequence continuity information corresponding to one of the multiple medical image sequences is unqualified, the integrity detection result corresponding to the medical image set is unqualified.

[0147] Specifically, if the sequence continuity information corresponding to each of the multiple medical image sequences is qualified, since the integrity test at the sequence orientation level of the medical image set is qualified and the continuity integrity test in each sequence is qualified, then the integrity test result of the medical image set is qualified, and the medical image set is determined to be a candidate medical image set for subsequent archiving.

[0148] If the sequence continuity information corresponding to one of the multiple medical image sequences is unqualified, it indicates that although the medical atlas passes the integrity test at the sequence orientation level, it fails the continuity integrity test in each sequence. The integrity test result of the medical image set is unqualified, and it is determined that the medical image set is not a candidate medical image set, and the medical image set is deleted from the IRC system.

[0149] In an embodiment of the present application, the coding information corresponding to each of the multiple medical images included in the medical image sequence is used to determine whether the codes corresponding to the multiple medical images are continuous to determine the sequence continuity information, and the integrity detection result corresponding to the medical image set is further determined by the sequence continuity information corresponding to each of the multiple medical image sequences in the medical image set.

[0150] Exemplary medical image upload device

[0151] Fig.11 The figure shows a schematic diagram of the structure of a medical image uploading device provided in an embodiment of the present application. The medical image uploading device provided in an embodiment of the present application is applied to a film reading system, and is used to upload a candidate medical image set corresponding to a visit examination of a subject collected by a research and development center to the visit item of the subject matching the candidate image in the IRC system.

[0152] Specifically, if Fig.11 As shown, the medical image uploading device 100 includes: a first determination module 101 , a second determination module 102 and an archiving module 103 .

[0153] The first determination module 101 is configured to determine basic image information corresponding to each of P candidate medical image sets obtained from the research center, wherein the P candidate medical image sets belong to the same subject; the second determination module 102 is configured to determine basic project information corresponding to a preset clinical trial project in the film reading system; the archiving module 103 is configured to archive the P candidate medical image sets into visit items corresponding to each of the P candidate medical image sets based on the basic image information and project basic information corresponding to each of the P candidate medical image sets.

[0154] Fig.12 FIG. 1 is a schematic diagram of the structure of an archiving module provided in an embodiment of the present application. Fig.12As shown, the archiving module 103 further includes: a first determination unit 1031, a subject matching unit 1032, a visit item matching unit 1033 and an archiving unit 1034.

[0155] The first determination unit 1031 is configured to determine the N subjects to which the P candidate medical image sets belong based on the basic image information corresponding to each of the P candidate medical image sets, so as to determine the M candidate medical image sets corresponding to each of the N subjects; the subject matching unit 1031 is configured to determine, for each of the N subjects, the subject matching relationship corresponding to the M candidate medical image sets based on the basic image information and project basic information corresponding to each of the M candidate medical image sets; the visit item matching unit 1032 is configured to determine the visit items corresponding to each of the M candidate medical image sets based on the subject matching relationship, the basic image information and project basic information corresponding to each of the M candidate medical image sets; the archiving unit 1033 is configured to archive the M candidate medical image sets into the visit items corresponding to each of the M candidate medical image sets based on the visit items corresponding to each of the M candidate medical image sets, so as to realize archiving the P candidate medical image sets into the visit items corresponding to each of the P candidate medical image sets.

[0156] Fig.13 FIG. 1 is a schematic diagram of the structure of a subject matching unit provided in an embodiment of the present application. Fig.13 As shown, the subject matching unit 1032 further includes: a first determining subunit 10321 , a second determining subunit 10322 , and a subject matching subunit 10323 .

[0157] The first determination subunit 10321 is configured to determine, based on the basic image information corresponding to each of the M candidate medical image sets, the subject information corresponding to the subjects to which the M candidate medical image sets belong; the second determination subunit 10322 is configured to determine, based on the project basic information, the subject information corresponding to each of the multiple subjects included in the clinical trial project; the subject matching subunit 10323 is configured to determine the subject matching relationship based on the subject information corresponding to the M candidate medical image sets and the subject information corresponding to each of the multiple subjects.

[0158] In one embodiment, when the subject matching relationship is that multiple subjects included in the clinical trial project are not matched with the subjects to which the M candidate medical image sets belong, the visit item matching unit 1033 is configured to establish multiple visit items corresponding to the subjects to which the M candidate medical image sets belong in the film reading system; determine the examination date information corresponding to each of the M candidate medical image sets based on the basic image information corresponding to each of the M candidate medical image sets; and for the multiple visit items established, determine the visit items corresponding to each of the M candidate medical image sets based on the examination date information and project basic information corresponding to each of the M candidate medical image sets.

[0159] In a further embodiment, the step of determining the visit items corresponding to each of the M candidate medical image sets based on the examination date information and project basic information corresponding to each of the M candidate medical image sets includes the following steps: determining the examination sequence information corresponding to the M candidate medical image sets based on the examination date information corresponding to each of the M candidate medical image sets; determining the earliest examination date as the baseline visit time based on the examination sequence information, and determining the visit item corresponding to the candidate medical image set corresponding to the earliest examination date as the baseline visit item; determining the visit interval information and the visit window information based on the project basic information; determining multiple follow-up visit items and the follow-up visit times corresponding to each of the multiple follow-up visit items based on the baseline visit time, the visit interval information and the visit window information; determining the follow-up visit items corresponding to each of the remaining candidate medical image sets in the M candidate medical image sets based on the multiple follow-up visit items and the follow-up visit times corresponding to each of the multiple follow-up visit items.

[0160] In another embodiment, the subject matching relationship is that a subject included in the clinical trial project is matched with a subject to which M candidate medical image sets belong, and the visit item matching unit 1033 is configured to determine the examination date information corresponding to each of the M candidate medical image sets; based on the project basic information, determine multiple follow-up visit items corresponding to the subjects matching the M candidate medical image sets, and the follow-up visit times corresponding to the multiple follow-up visit items; based on the examination date information corresponding to each of the M candidate medical image sets and the follow-up visit times corresponding to each of the multiple follow-up visit items, determine the follow-up visit items corresponding to each of the M candidate medical image sets.

[0161] Fig.14 FIG. 1 is a schematic diagram of the structure of a medical image uploading device provided by an embodiment of the present application. Fig.14 As shown, the medical image uploading device 100 also includes a visit status determination module 104 and a display module 105. The visit status determination module 104 is configured to update the visit status information of the subject based on the archiving results corresponding to each of the P candidate medical image sets, and the display module 105 is configured to present the updated visit status information.

[0162] In one embodiment, Fig.14 As shown, the medical image uploading device 100 also includes a judgment module 106 and a sending module 107. The judgment module 106 is configured to judge whether there is any abnormality in the visit status information; the sending module 107 is configured to send a warning message to the research center if there is any abnormality in the visit status information.

[0163] Fig.15 FIG. 1 is a schematic diagram of the structure of a medical image uploading device provided by an embodiment of the present application. Fig.15 As shown, the medical image uploading device 100 further includes a first judgment module 108 , a first execution module 109 and a second execution module 110 .

[0164] The first judgment module 108 is configured to determine, for each medical image set in the multiple medical image sets received by the film reading system, whether the project identification information corresponding to the medical image set is the same as the project identification information corresponding to the preset clinical trial project in the film reading system; the first execution module 109 is configured to, if not, delete the medical image set; the second execution module 110 is configured to, if so, determine the completeness detection result corresponding to the medical image set based on the basic image information corresponding to the medical image set, and determine whether the medical image set is a candidate medical image set based on the completeness detection result corresponding to the medical image set.

[0165] In one embodiment, the second execution module 110 is further configured to, if the project identification information corresponding to the medical image set is the same as the project identification information corresponding to the preset clinical trial project in the film reading system, determine the completeness detection result corresponding to the medical image set based on the basic image information corresponding to the medical image set; if the completeness detection result corresponding to the medical image set is qualified, determine the medical image set as a candidate medical image set; if the completeness detection result corresponding to the medical image set is unqualified, determine that the medical image set is not a candidate medical image set, and delete the medical image set.

[0166] Fig.16 FIG. 1 is a schematic diagram of the structure of a second execution module provided in an embodiment of the present application. Fig.16 As shown, the second execution module 110 further includes a second determination unit 1101 , a first judgment unit 1102 , a first execution unit 1103 and a second execution unit 1104 .

[0167] The second determination unit 1101 is configured to determine, based on the basic image information corresponding to the medical image set, the slice position information corresponding to each of the multiple medical image sequences included in the medical image set; the first judgment unit 1102 is configured to judge, based on the slice position information corresponding to each of the multiple medical image sequences, whether the anatomical position order corresponding to the multiple medical image sequences is correct; the first execution unit 1103 is configured to, if not, determine that the integrity detection result is unqualified; the second execution unit 1104 is configured to, if so, determine the sequence continuity information corresponding to each of the multiple medical image sequences based on the basic image information corresponding to the medical image set, so as to further determine the integrity detection result corresponding to the medical image set.

[0168] Fig.17 FIG. 1 is a schematic diagram of the structure of a second execution module provided in an embodiment of the present application. Fig.17 As shown, the second execution unit 1104 further includes a third determination subunit 11041 , a first judgment subunit 11042 , a first execution subunit 11043 and a first execution subunit 11044 .

[0169] The third determination subunit 11041 is configured to determine, for each medical image sequence in a plurality of medical image sequences, the coding information corresponding to each of the plurality of medical images included in the medical image sequence; the first judgment subunit 11042 is configured to judge, based on the coding information corresponding to the plurality of medical images, whether the coding corresponding to the plurality of medical images is continuous, so as to determine the sequence continuity information; the first execution subunit 11043 is configured to, if the sequence continuity information corresponding to the plurality of medical image sequences is qualified, the integrity detection result corresponding to the medical image set is qualified; the second execution subunit 11043 is configured to, if the sequence continuity information corresponding to one of the plurality of medical image sequences is unqualified, the integrity detection result corresponding to the medical image set is unqualified.

[0170] The specific functions and operations of the other modules in the above medical image upload device have been described above. Figures 1 to 10 The medical image uploading method described in detail is described in detail, so its repeated description will be omitted here.

[0171] Exemplary Electronic Devices

[0172] Fig.18 FIG. 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Fig.18 As shown, electronic device 300 includes one or more processors 310 and memory 320 .

[0173] 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.

[0174] 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, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a 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 uploading method of each embodiment of the present application described above and / or other desired functions.

[0175] 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).

[0176] Of course, to simplify, Fig.18 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, according to specific application situations, the electronic device 300 may also include any other appropriate components.

[0177] Exemplary computer program products and computer-readable storage media

[0178] 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 uploading method provided according to each embodiment of the present application described in the above-mentioned "Exemplary Medical Image Uploading Method" section of this specification.

[0179] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and also conventional step-by-step programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0180] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the medical image uploading method provided according to each embodiment of the present application described in the above “Exemplary Medical Image Uploading Method” section of this specification.

[0181] 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 include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. 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 of the above.

[0182] 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 there are many similar variations. All variations directly derived or associated from the contents disclosed in the present application by those skilled in the art should fall within the protection scope of the present application.

[0183] It should be understood that the qualifiers such as first and second 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.

[0184] The above are only preferred embodiments of the present application and are not intended to limit the protection scope 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 protection scope of the present application.

Claims

1. A method for uploading medical images, characterized in that: Applied to a film reading system, the method comprises: Determine the basic image information corresponding to each of the P candidate medical image sets obtained from the research center; Determine the basic project information corresponding to the preset clinical trial project in the film reading system; Based on the basic image information and the project basic information corresponding to each of the P candidate medical image sets, the P candidate medical image sets are respectively filed into the visit items corresponding to each of the P candidate medical image sets, wherein the visit items are used to characterize the stage of the visit examination performed by the subject; The step of filing the P candidate medical image sets into the visit items corresponding to the P candidate medical image sets based on the basic image information and the project basic information respectively corresponding to the P candidate medical image sets includes: Based on basic image information corresponding to each of the P candidate medical image sets, determine N subjects to which the P candidate medical image sets belong, so as to determine M candidate medical image sets corresponding to each of the N subjects; For each of the N subjects, based on the basic image information and the project basic information corresponding to each of the M candidate medical image sets, determining a subject matching relationship corresponding to the M candidate medical image sets; Determine the visit items corresponding to each of the M candidate medical image sets based on the subject matching relationship, the basic image information corresponding to each of the M candidate medical image sets, and the basic item information; Based on the visit items corresponding to the M candidate medical image sets, the M candidate medical image sets are respectively filed into the visit items corresponding to the M candidate medical image sets, so as to respectively file the P candidate medical image sets into the visit items corresponding to the P candidate medical image sets; The determining of the subject matching relationship corresponding to the M candidate medical image sets based on the basic image information and the project basic information corresponding to each of the M candidate medical image sets includes: Determine, based on the basic image information corresponding to each of the M candidate medical image sets, subject information corresponding to the subject to which the M medical image sets to be uploaded belong; Based on the basic information of the project, determining subject information corresponding to each of the multiple subjects included in the clinical trial project; The subject matching relationship is determined based on the subject information corresponding to the M candidate medical image sets and the subject information corresponding to each of the multiple subjects.

2. The medical image uploading method according to claim 1, characterized in that: The subject matching relationship includes that a plurality of subjects included in the clinical trial project do not match the subjects to which the M candidate medical image sets belong, wherein determining the visit items corresponding to each of the M candidate medical image sets based on the subject matching relationship, basic image information corresponding to each of the M candidate medical image sets, and the project basic information includes: Establishing, in the image reading system, a plurality of visit items corresponding to the subjects to which the M candidate medical image sets belong; Determining the examination date information corresponding to each of the M candidate medical image sets based on the basic image information corresponding to each of the M candidate medical image sets; For the multiple visit items established, based on the examination date information corresponding to each of the M candidate medical image sets and the project basic information, the visit items corresponding to each of the M candidate medical image sets are determined.

3. The medical image uploading method according to claim 2, characterized in that: The determining, based on the examination date information and the basic project information corresponding to each of the M candidate medical image sets, the visit items corresponding to each of the M candidate medical image sets comprises: Determine, based on the examination date information corresponding to each of the M candidate medical image sets, the examination sequence information corresponding to each of the M candidate medical image sets; Based on the examination sequence information, the earliest examination date is determined as the baseline visit time, and the visit item corresponding to the medical image set to be uploaded corresponding to the earliest examination date is determined as the baseline visit item; Based on the basic information of the project, determine the visit interval information and the visit window information; Determine a plurality of follow-up visit items and the follow-up visit times corresponding to the plurality of follow-up visit items based on the baseline visit time, the visit interval information and the visit window information; Based on the multiple follow-up visit items and the follow-up visit times corresponding to the multiple follow-up visit items, the follow-up visit items corresponding to the remaining candidate medical image sets in the M candidate medical image sets are determined.

4. The medical image uploading method according to claim 1, characterized in that: The subject matching relationship includes matching between a subject included in the clinical trial project and a subject to which the M candidate medical image sets belong, wherein determining the visit items corresponding to the M candidate medical image sets based on the subject matching relationship, basic image information corresponding to each of the M candidate medical image sets, and the project basic information includes: Determine the examination date information corresponding to each of the M candidate medical image sets; Based on the basic project information, determine a plurality of follow-up visit items corresponding to the subjects matching the M candidate medical image sets, and a follow-up visit time corresponding to each of the plurality of follow-up visit items; Based on the examination date information corresponding to each of the M candidate medical image sets and the follow-up visit times corresponding to each of the multiple follow-up visit items, the follow-up visit items corresponding to each of the M candidate medical image sets are determined.

5. The medical image uploading method according to claim 1, characterized in that: After the P candidate medical image sets are filed respectively into the visit items corresponding to the P candidate medical images, the method further includes: Based on the archiving results corresponding to each of the P candidate medical image sets, updating the visit status information of the subject; The updated visit status information is presented.

6. The medical image uploading method according to claim 4, characterized in that: Also includes: Determine whether the visit status information is abnormal; If so, send a warning message to the research center.

7. The medical image uploading method according to claim 1, characterized in that: Before determining the basic image information corresponding to each of the P candidate medical image sets in the image reading system, the method further includes: For each of the plurality of medical image sets received by the image reading system, determining whether the project identification information corresponding to the medical image set is the same as the project identification information corresponding to the preset clinical trial project in the image reading system, If not, deleting the medical image set; If so, based on the basic image information corresponding to the medical image set, determine the completeness detection result corresponding to the medical image set, and based on the completeness detection result corresponding to the medical image set, determine whether the medical image set is the candidate medical image set.

8. The medical image uploading method according to claim 7, characterized in that: The determining, based on the completeness detection result corresponding to the medical image set, whether the medical image set is the candidate medical image set comprises: If the integrity detection result corresponding to the medical image set is qualified, determining the medical image set as the candidate medical image set; If the integrity detection result corresponding to the medical image set is unqualified, it is determined that the medical image set is not the candidate medical image set, and the medical image set is deleted.

9. The medical image uploading method according to claim 8, characterized in that: The determining, based on the basic image information corresponding to the medical image set, a completeness detection result corresponding to the medical image set comprises: Determining slice position information corresponding to each of a plurality of medical image sequences included in the medical image set based on basic image information corresponding to the medical image set; Based on the slice position information corresponding to each of the plurality of medical image sequences, determining whether the anatomical position sequence corresponding to the plurality of medical image sequences is correct; If not, determining that the integrity test result is unqualified; If so, based on the basic image information corresponding to the medical image set, the sequence continuity information corresponding to each of the plurality of medical image sequences is determined to further determine the completeness detection result corresponding to the medical image set.

10. The medical image uploading method according to claim 9, characterized in that: The determining, based on the basic image information corresponding to the medical image set, the sequence continuity information corresponding to each of the plurality of medical image sequences to further determine the integrity detection result corresponding to the medical image set includes: For each medical image sequence in the multiple medical image sequences, determining encoding information corresponding to each of the multiple medical images included in the medical image sequence; Based on the coding information corresponding to the multiple medical images, determining whether the codes corresponding to the multiple medical images are continuous to determine the sequence continuity information; If the sequence continuity information corresponding to each of the plurality of medical image sequences is qualified, the integrity detection result corresponding to the medical image set is qualified; If the sequence continuity information corresponding to one of the multiple medical image sequences is unqualified, the integrity detection result corresponding to the medical image set is unqualified.

11. A medical image uploading device, characterized in that: Applied to a film reading system, the device comprises: A first determination module is configured to determine basic image information corresponding to each of the P candidate medical image sets in the image reading system; A second determination module is configured to determine basic project information corresponding to a preset clinical trial project in the film reading system; an archiving module, configured to archive the P candidate medical image sets into visit items corresponding to the P candidate medical image sets respectively based on the basic image information corresponding to the P candidate medical image sets and the basic project information, wherein the visit items are used to characterize the stages of the visit examinations performed by the subjects; Wherein, the archiving module includes a first determination unit, a subject matching unit, a visit item matching unit and an archiving unit; The first determining unit is configured to determine, based on basic image information corresponding to each of the P candidate medical image sets, the N subjects to which the P candidate medical image sets belong, so as to determine the M candidate medical image sets corresponding to each of the N subjects; The subject matching unit is configured to determine, for each subject among the N subjects, a subject matching relationship corresponding to the M candidate medical image sets based on the image basic information and the project basic information corresponding to each of the M candidate medical image sets; The visit item matching unit is configured to determine the visit items corresponding to each of the M candidate medical image sets based on the subject matching relationship, the basic image information and the basic item information corresponding to each of the M candidate medical image sets; The filing unit is configured to file the M candidate medical image sets into the visit items corresponding to the M candidate medical image sets, respectively, based on the visit items corresponding to the M candidate medical image sets, so as to file the P candidate medical image sets into the visit items corresponding to the P candidate medical image sets, respectively; The determining of the subject matching relationship corresponding to the M candidate medical image sets based on the basic image information and the basic project information corresponding to each of the M candidate medical image sets includes: Based on the basic image information corresponding to each of the M candidate medical image sets, determining the subject information corresponding to the subject to which the M medical image sets to be uploaded belong; Based on the basic information of the project, determining subject information corresponding to each of the multiple subjects included in the clinical trial project; The subject matching relationship is determined based on the subject information corresponding to the M candidate medical image sets and the subject information corresponding to each of the multiple subjects.

12. 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 executes the medical image uploading method according to any one of claims 1 to 10.

13. 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 enabled to execute the medical image uploading method according to any one of claims 1 to 10.

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