A Web-based medical image retrieval method and system, a computer device and a storage medium

Abstract

The application discloses a kind of based on Web's medical image call-up method, system, computer equipment and storage medium, belong to image loading technical field.The method includes: in response to examination request, the first item of each sequence corresponding to examination request is obtained from server based on system minimum design concurrency;In response to sequence viewing request, the CPU core number and downstream bandwidth of current device are obtained through browser interface, obtain target concurrency, and the image loading task of corresponding sequence viewing request is executed based on target concurrency;After the execution of current image loading task is completed, the response time and failure rate of recent several image loading tasks are obtained, target concurrency is dynamically adjusted based on response time and failure rate, obtain the target concurrency of next moment, and the image loading task of next moment is executed based on the target concurrency of next moment.The application can improve the speed and system stability of medical image remote call-up.

Description

Technical Field

[0001] This invention belongs to the field of image loading technology and relates to a web-based method, system, computer device, and storage medium for accessing medical images. Background Technology

[0002] With the rapid development of telemedicine and hierarchical medical systems, remote diagnosis, remote consultation, and remote teaching of medical images have become important components of the modern medical system. Especially in application scenarios such as regional imaging centers, medical alliances, and specialist alliances, experts from higher-level hospitals need to remotely access imaging data uploaded by lower-level or primary healthcare institutions for remote image reading, consultation, and teaching guidance.

[0003] Against this backdrop, traditional client-based (C / S architecture) PACS systems, due to their complex deployment, strong platform dependence, and limited remote access, are no longer sufficient to meet the needs of remote diagnosis. In contrast, web-based medical image browsers allow direct access to image data through a browser, eliminating the need for client installation, supporting cross-platform use, and offering advantages such as flexible deployment, easy maintenance, and low access costs. They are gradually becoming the core technology direction for remote image diagnosis.

[0004] Medical imaging data is typically stored on servers, and the system accesses the data through an interface. When a user selects a specific examination, the front-end browser sends an HTTP request to the back-end to retrieve image metadata and image frames. To reduce initial load latency, existing systems generally employ an on-demand caching strategy. That is, the system only begins requesting all image frames for a sequence after the user clicks on it. Loaded images are usually stored in the browser's memory cache so that they don't need to be reloaded when the user views them again. Based on the browser's HTTP request mechanism, browsers (such as Chrome) typically limit the number of concurrent requests to the same domain to six. When the system needs to load a large number of image frames (e.g., a CT or MRI sequence containing hundreds of frames), the browser automatically queues the requests and initiates them sequentially. To maximize loading speed, existing technologies often employ a fixed concurrency strategy. For example, in OHIFF Viewer, the default setting is to load six image frames concurrently. However, this fixed strategy ignores the differences in hardware performance of user terminals. On low-performance devices (such as ordinary laptops), concurrently loading six high-resolution images can cause excessive CPU and memory usage, leading to page lag or even crashes. Existing systems often employ a sequential caching strategy when performing caching tasks. This means that the caching of the next sequence will not begin until all images in the current sequence have been loaded. If a user switches to the next sequence before the previous one has finished loading, the system must wait for the previous task to complete before starting a new caching task. This loading method results in long waiting times and less smooth interaction for users in multi-sequence browsing scenarios. If network fluctuations cause a frame image request to fail, the browser typically reports an error or marks the sequence as unavailable. Due to the lack of an effective automatic retry or manual reload mechanism, users often need to reopen and check to reload the failed images, which can easily lead to problems such as missing parts of the image and incomplete diagnostic information. Summary of the Invention

[0005] The purpose of this invention is to provide a web-based method, system, computer device, and storage medium for accessing medical images, in order to solve the problem that current remote access methods for medical images cannot be adapted to the performance of the device, resulting in unsmooth image loading or wasted device performance.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] In a first aspect, the present invention provides a Web-based method for accessing medical images, comprising the following steps:

[0008] In response to an inspection request, the system retrieves the first item of each sequence corresponding to the inspection request from the server based on the minimum concurrency of the system design; the first item of the sequence corresponds to a thumbnail of the sequence, and the user clicks on any thumbnail to trigger the corresponding sequence viewing request;

[0009] In response to a sequence viewing request, the system obtains the current number of CPU cores and downlink bandwidth of the device through the browser interface, determines the optimal concurrency of the device based on the number of CPU cores, adjusts the optimal concurrency based on the downlink bandwidth to obtain the target concurrency, and executes the image loading task corresponding to the sequence viewing request based on the target concurrency.

[0010] After the current image loading task is completed, obtain the response time and failure rate of the most recent image loading tasks, dynamically adjust the target concurrency based on the response time and failure rate, obtain the target concurrency for the next time step, and execute the image loading task for the next time step based on the target concurrency for the next time step.

[0011] The method for determining the optimal concurrency of a device based on the number of CPU cores is as follows:

[0012] When M≤6, N1 = minimum design concurrency of the system;

[0013] When 7≤M≤9, N1 = the first design concurrency of the system;

[0014] When 10≤M≤15, N1 = the second design concurrency of the system;

[0015] When M≥16, N1 = the maximum design concurrency of the system;

[0016] Where M represents the number of CPU cores and N1 represents the optimal concurrency.

[0017] The method to obtain the target concurrency by adjusting the optimal concurrency based on downlink bandwidth is as follows:

[0018] If 1Mbps≤B, N2 = minimum system design concurrency;

[0019] If 1Mbps < B ≤ 5Mbps, N2 = MAX(1, 0.5 × N1).

[0020] If B > 5Mbps, N2 = N1;

[0021] In the formula, B represents the downlink bandwidth, N2 represents the target concurrency, and MAX() represents the maximum value function.

[0022] The method for dynamically adjusting the target concurrency based on response time and failure rate to obtain the target concurrency at the next moment is as follows:

[0023] If T > 1500ms or E > 10%, then reduce the target concurrency by 1, down to the minimum designed concurrency of the system.

[0024] If T < 500ms or E < 5%, then increase the target concurrency by 1, up to the device's optimal concurrency.

[0025] Otherwise, keep the target concurrency level unchanged;

[0026] Where T represents response time and E represents failure rate.

[0027] If the number of CPU cores of the current device cannot be obtained, the number of CPU cores of the device is recorded as a preset value, which is 4.

[0028] If a new sequence viewing request is received during the execution of an image loading task, the image loading task for the current sequence is paused, and the corresponding image loading task is executed based on the new sequence viewing request.

[0029] If an image loading task fails during the execution of an image loading task, it will be automatically reloaded three times. If all three automatic reloads fail, an error placeholder will be rendered at the corresponding position of the image on the front-end page, and a manual loading interaction button will be displayed.

[0030] Secondly, the present invention provides a web-based medical image retrieval system, comprising:

[0031] The inspection module, in response to an inspection request, retrieves the first item of each sequence corresponding to the inspection request from the server based on the minimum concurrency of the system design; the first item of the sequence corresponds to a thumbnail of the sequence, and the user clicks on any thumbnail to trigger the corresponding sequence viewing request;

[0032] The sequence module, in response to sequence viewing requests, executes the corresponding image loading task based on the target concurrency level for each sequence viewing request;

[0033] The parameter acquisition module obtains the current device's CPU core count and downlink bandwidth, as well as the response time and failure rate of the most recent image loading tasks, through the browser interface.

[0034] The concurrency calculation module determines the optimal concurrency of the device based on the number of CPU cores; adjusts the optimal concurrency based on downlink bandwidth to obtain the target concurrency; and dynamically adjusts the target concurrency based on response time and failure rate to obtain the target concurrency for the next moment.

[0035] Thirdly, the present invention provides a computer device, comprising:

[0036] Memory, used to store computer instructions;

[0037] A processor is configured to execute the computer instructions to implement the steps of the above-described Web-based medical image retrieval method.

[0038] Fourthly, the present invention provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the above-described Web-based medical image retrieval method.

[0039] Beneficial effects

[0040] The Web-based medical image retrieval method of the present invention determines the optimal and target concurrency of the system based on device parameters, and dynamically adjusts the target concurrency in real time according to response time and failure rate. This effectively copes with network fluctuations, realizes dynamic resource scheduling, improves the stability of image retrieval, and achieves a balance between loading speed and resource consumption. It also effectively avoids lag on low-configuration devices and resource waste on high-performance devices. Attached Figure Description

[0041] Figure 1 This is a flowchart of a web-based medical image retrieval method according to the present invention. Detailed Implementation

[0042] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0043] Example 1

[0044] refer to Figure 1 As shown, a web-based method for accessing medical images includes the following steps:

[0045] Step S1: Obtain the inspection request. In response to the inspection request, obtain the first item of each sequence corresponding to the inspection request from the server based on the minimum concurrency of the system design.

[0046] In this embodiment, the system is initialized according to the inspection request, and the system enters a low-speed background cache mode. In the low-speed background cache mode, the system loads the first frame of each sequence in sequence order.

[0047] A single inspection contains multiple sequences (e.g., T1, T2, etc.), each consisting of dozens or even hundreds of slice images. The first image of the sequence is the first frame of the sequence, usually used as the cover thumbnail of the sequence for visual preview in the sequence navigation bar.

[0048] In low-speed background caching mode, the system background concurrency is the minimum designed concurrency, which is 1 in this embodiment. The system only loads the first frame of the sequence, which can quickly render the thumbnails of the sequence navigation bar with extremely low traffic and bandwidth consumption, allowing users to instantly see the overall picture of the entire sequence being checked, making it convenient for users to query. Users can select to view the corresponding image in the sequence based on the information in the first frame of the sequence, and clicking on any thumbnail triggers the corresponding sequence viewing request.

[0049] Step S2: In response to the sequence viewing request, obtain and determine the target concurrency based on the device parameters, and execute the image loading task corresponding to the sequence viewing request based on the target concurrency.

[0050] In this embodiment, the system enters a high-priority loading mode based on the sequence viewing request; the number of CPU cores and downlink bandwidth of the current device are obtained through the browser interface, and the optimal concurrency of the device is determined based on the number of CPU cores; the optimal concurrency is adjusted based on the downlink bandwidth to obtain the target concurrency.

[0051] In this embodiment, the system obtains the number of CPU cores M of the current device (M is an integer) through the browser interface. If the acquisition fails, M=4.

[0052] The method for determining the optimal concurrency N1 for a device based on the number of CPU cores is as follows:

[0053] When M≤6, N1=1, which is the minimum design concurrency of the system to avoid excessive load on low-configuration devices, which could cause the system to freeze.

[0054] When 7≤M≤9, N1=2;

[0055] When 10≤M≤15, N1=4;

[0056] When M≥16, N1=6, which is the maximum design concurrency of the system, ensuring that high-configuration devices can execute loading tasks faster.

[0057] The method to obtain the target concurrency N2 by adjusting the optimal concurrency based on the downlink bandwidth B is as follows:

[0058] If 1Mbps≤B, N2=1;

[0059] If 1Mbps < B ≤ 5Mbps, N2 = MAX(1, 0.5 × N1).

[0060] If B > 5Mbps, then N2 = N1.

[0061] Step S3: After the current image loading task is completed, obtain the response time and failure rate of the most recent image loading tasks, dynamically adjust the target concurrency based on the response time and failure rate to obtain the target concurrency for the next time step, and execute the image loading task for the next time step based on the target concurrency for the next time step.

[0062] During image loading, the system monitors the initiation time, end time, and end status of each image loading task in real time. The end status is either success or failure. The average response time T = (end time - initiation time) / total number of image loading tasks. The error rate E = number of failures / total number of image loading tasks.

[0063] If the first adjustment condition is met: T > 1500ms or E > 10%, then the target concurrency will be reduced by 1, with a minimum reduction to 1.

[0064] If the second adjustment condition is met: T < 500ms or E < 5%, then the target concurrency will be increased by 1, up to the maximum system concurrency.

[0065] Otherwise, keep the target concurrency level unchanged.

[0066] If a new sequence viewing request is received during the execution of an image loading task, the image loading task for the current sequence is paused, and the corresponding image loading task is executed based on the new sequence viewing request.

[0067] Repeat step S3 until all images in the current sequence are loaded, at which point the system returns to a low-speed background caching mode.

[0068] When a user sends a request to actively exit the high-priority loading mode, that is, to end the current sequence viewing request, the system ends the current image loading task and the system resumes the low-speed background caching mode.

[0069] If an image loading task fails during the execution of an image loading task, it will be automatically reloaded three times. If all three automatic reloads fail, an error placeholder will be rendered at the corresponding position of the image on the front-end page, and a manual loading interactive button will be displayed.

[0070] When the manual reload button is pressed, the image is reloaded. If the reload is successful, the original error placeholder is replaced with the loaded image. If the reload fails, a prompt message is displayed, and the manual reload button remains available.

[0071] The Web-based medical image retrieval method of the present invention determines the optimal and target concurrency of the system based on device parameters, and dynamically adjusts the target concurrency in real time according to response time and failure rate. This effectively copes with network fluctuations, realizes dynamic resource scheduling, improves the stability of image retrieval, and achieves a balance between loading speed and resource consumption. It also effectively avoids lag on low-configuration devices and resource waste on high-performance devices.

[0072] Example 2

[0073] A web-based medical image retrieval system includes:

[0074] The inspection module, in response to an inspection request, retrieves the first item of each sequence corresponding to the inspection request from the server based on the minimum concurrency of the system design; the first item of the sequence corresponds to a thumbnail of the sequence, and the user clicks on any thumbnail to trigger the corresponding sequence viewing request;

[0075] The sequence module, in response to sequence viewing requests, executes the corresponding image loading task based on the target concurrency level for each sequence viewing request;

[0076] The parameter acquisition module obtains the current device's CPU core count and downlink bandwidth, as well as the response time and failure rate of the most recent image loading tasks, through the browser interface.

[0077] The concurrency calculation module determines the optimal concurrency of the device based on the number of CPU cores; adjusts the optimal concurrency based on downlink bandwidth to obtain the target concurrency; and dynamically adjusts the target concurrency based on response time and failure rate to obtain the target concurrency for the next moment.

[0078] Example 3

[0079] A computer device, comprising:

[0080] Memory, used to store computer instructions;

[0081] A processor is configured to execute the computer instructions to implement the steps of the Web-based medical image retrieval method described in Embodiment 1.

[0082] Example 4

[0083] A computer-readable storage medium storing computer instructions that, when executed by a processor, implement the steps of the Web-based medical image retrieval method described in Embodiment 1.

[0084] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0085] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0086] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0087] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0088] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A Web-based method for accessing medical images, characterized in that, Includes the following steps: In response to an inspection request, the system retrieves the first item of each sequence corresponding to the inspection request from the server based on the minimum concurrency of the system design; the first item of the sequence corresponds to a thumbnail of the sequence, and the user clicks on any thumbnail to trigger the corresponding sequence viewing request; In response to a sequence viewing request, the system obtains the current number of CPU cores and downlink bandwidth of the device through the browser interface, determines the optimal concurrency of the device based on the number of CPU cores, adjusts the optimal concurrency based on the downlink bandwidth to obtain the target concurrency, and executes the image loading task corresponding to the sequence viewing request based on the target concurrency. After the current image loading task is completed, obtain the response time and failure rate of the most recent image loading tasks, dynamically adjust the target concurrency based on the response time and failure rate, obtain the target concurrency for the next time step, and execute the image loading task for the next time step based on the target concurrency for the next time step.

2. The Web-based medical image retrieval method according to claim 1, characterized in that, The method for determining the optimal concurrency of a device based on the number of CPU cores is as follows: When M≤6, N1 = minimum design concurrency of the system; When 7≤M≤9, N1 = the first design concurrency of the system; When 10≤M≤15, N1 = the second design concurrency of the system; When M≥16, N1 = the maximum design concurrency of the system; Where M represents the number of CPU cores and N1 represents the optimal concurrency.

3. The Web-based medical image retrieval method according to claim 2, characterized in that, The method to obtain the target concurrency by adjusting the optimal concurrency based on downlink bandwidth is as follows: If 1Mbps≤B, N2 = minimum system design concurrency; If 1Mbps < B ≤ 5Mbps, N2 = MAX(1, 0.5 × N1). If B > 5Mbps, N2 = N1; In the formula, B represents the downlink bandwidth, N2 represents the target concurrency, and MAX() represents the maximum value function.

4. The Web-based medical image retrieval method according to claim 3, characterized in that, The method for dynamically adjusting the target concurrency based on response time and failure rate to obtain the target concurrency at the next moment is as follows: If T > 1500ms or E > 10%, then reduce the target concurrency by 1, down to the minimum designed concurrency of the system. If T < 500ms or E < 5%, then increase the target concurrency by 1, up to the device's optimal concurrency. Otherwise, keep the target concurrency level unchanged; Where T represents response time and E represents failure rate.

5. The Web-based medical image retrieval method according to claim 1, characterized in that, If the number of CPU cores of the current device cannot be obtained, the number of CPU cores of the device is recorded as a preset value, which is 4.

6. The Web-based medical image retrieval method according to claim 1, characterized in that, If a new sequence viewing request is received during the execution of an image loading task, the image loading task for the current sequence is paused, and the corresponding image loading task is executed based on the new sequence viewing request.

7. The Web-based medical image retrieval method according to claim 1, characterized in that, If an image loading task fails during the execution of an image loading task, it will be automatically reloaded three times. If all three automatic reloads fail, an error placeholder will be rendered at the corresponding position of the image on the front-end page, and a manual loading interaction button will be displayed.

8. A web-based medical image retrieval system, characterized in that, include: The inspection module, in response to inspection requests, retrieves the first item of each sequence corresponding to the inspection request from the server based on the minimum concurrency limit designed for the system. The first item of the sequence corresponds to a thumbnail of the sequence. When a user clicks on any thumbnail, a request to view the corresponding sequence is triggered. The sequence module, in response to sequence viewing requests, executes the corresponding image loading task based on the target concurrency level for each sequence viewing request; The parameter acquisition module obtains the current device's CPU core count and downlink bandwidth, as well as the response time and failure rate of the most recent image loading tasks, through the browser interface. The concurrency calculation module determines the optimal concurrency of the device based on the number of CPU cores; adjusts the optimal concurrency based on downlink bandwidth to obtain the target concurrency; and dynamically adjusts the target concurrency based on response time and failure rate to obtain the target concurrency for the next moment.

9. A computer device, characterized in that, include: Memory, used to store computer instructions; A processor for executing the computer instructions to implement the steps of the Web-based medical image retrieval method according to any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by a processor, the computer instructions implement the steps of the Web-based medical image retrieval method as described in any one of claims 1-7.

Images