An intelligent medical image evaluation system

Abstract

The present application relates to the field of medical imaging technology, and in particular to a medical imaging intelligent film evaluation system, which includes: a data acquisition module for acquiring a patient position image sequence, imaging device operation data and device operation environment data, and simultaneously acquiring patient body thickness data; an image registration module for performing image registration on a patient position image sequence; a position jitter assessment module for assessing the patient's position jitter degree; a scanning range assessment module for assessing the scanning range matching degree; an equipment operation assessment module for assessing the imaging device operation stability; an imaging quality estimation module for analyzing the position jitter degree, scanning range matching degree and imaging device operation stability, and estimating the imaging quality of medical images. The present application improves the accuracy and reliability of medical image quality assessment by quantitatively analyzing the patient's position jitter and the imaging device operation status.

Description

Technical Field

[0001] The present application relates to the field of medical imaging technology, and in particular to an intelligent medical imaging evaluation system. Background Art

[0002] Medical imaging plays an important role in disease screening, abnormality detection, disease diagnosis, treatment planning and prognosis monitoring. With the advancement of medical imaging equipment and imaging technology, more and more imaging modalities are being used in clinical aspects, such as computed radiography (CR), digital radiography (DR), computed tomography (CT), and magnetic resonance imaging (MRI). The quality of medical imaging is directly related to the accuracy of diagnostic reports and treatment activities. Quality control is an important link in ensuring image quality and medical safety.

[0003] The existing technology usually relies on manual interpretation or evaluation based on image parameters when evaluating the quality of medical images. Manual evaluation is time-consuming and labor-intensive, and is greatly affected by the subjective factors of the evaluator, and there are subjective judgment differences. The evaluation method based on image parameters ignores the influence of patient factors and imaging equipment factors on the quality evaluation of medical images during the medical image scanning process. For example, the shaking of the patient's body during the scanning process will produce artifacts such as blurring and ghosting, resulting in a decrease in image quality, and the stability of equipment operation will also be directly related to the clarity of the image. Therefore, in order to improve the accuracy of medical image quality evaluation, the present application provides a medical image intelligent film evaluation system. Summary of the invention

[0004] In order to overcome the defects and shortcomings of the prior art, the present application provides a medical image intelligent evaluation system, which improves the accuracy and reliability of medical image quality assessment by quantitatively analyzing the patient's body position jitter and the operating status of the imaging device.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a medical image intelligent evaluation system, including a data acquisition module, an image registration module, a body position jitter evaluation module, a scanning range evaluation module, an equipment operation evaluation module and an imaging quality estimation module;

[0007] The data acquisition module is used to acquire the patient's body position image sequence, imaging equipment operation data and equipment operation environment data during the medical imaging scanning process, and to acquire the patient's body thickness data;

[0008] The image registration module is used to perform image registration on the acquired patient body position image sequence, and send the registered patient body position image sequence to the body position jitter assessment module;

[0009] The body position jitter assessment module is used to analyze the registered patient body position image sequence to obtain the patient's body position jitter degree;

[0010] The scanning range evaluation module is used to analyze the patient's body thickness data and the imaging device operation data to obtain the scanning range matching degree;

[0011] The equipment operation evaluation module is used to analyze the imaging equipment operation data and the equipment operation environment data to obtain the imaging equipment operation stability;

[0012] The imaging quality estimation module is used to analyze the degree of body position jitter, the degree of scanning range matching and the operating stability of the imaging device, and to estimate the imaging quality of the medical image.

[0013] Optionally, the specific evaluation steps of the body position jitter evaluation module include:

[0014] Acquire a registered patient position image sequence;

[0015] Extracting jitter data in the patient's body position images at adjacent acquisition moments through the patient's body position image sequence, the jitter data including jitter displacement, jitter velocity and jitter angular velocity;

[0016] The body position jitter index is calculated based on the patient's jitter data. The body position jitter index is used to quantify the patient's body position jitter degree. The calculation formula of the body position jitter index is:

[0017] ;

[0018] In the formula express The jitter displacement at the moment, represents the mean jitter displacement of the patient during the medical imaging scan. represents the medical image scanning time, express The jitter speed of the moment, represents the mean shaking speed of the patient during the medical imaging scan. express The angular velocity of the vibration at the moment, represents the mean angular velocity of the patient's jitter during medical imaging scanning, represents the jitter displacement weight, represents the jitter speed weight, represents the jitter angular velocity weight, Indicates the body position jitter index.

[0019] Optionally, extracting jitter data from patient body position images at adjacent acquisition moments includes:

[0020] Acquire patient position image sequence Patient position image at any time and Patient position image at any time ;

[0021] Patient position image and patient position images Calculate the patient jitter data. The calculation formula for the patient jitter data is:

[0022] ;

[0023] In the formula Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Represents the number of pixels in the patient position image, express The jitter displacement at the moment, Indicates the time interval between adjacent collection times, express The jitter speed of the moment, Indicates Pixels in The jitter angle at the moment, Indicates Pixels in The jitter angle at the moment, express The jitter angular velocity at the moment.

[0024] Optionally, the specific evaluation steps of the scanning range evaluation module include:

[0025] Acquire patient body thickness data and device longitudinal scanning range data from imaging device operation data;

[0026] The scanning range matching index is calculated by using the patient's body thickness data and the longitudinal scanning range data. The scanning range matching index is used to quantify the matching degree between the longitudinal scanning range of the imaging device and the patient's body thickness. The calculation formula of the scanning range matching index is:

[0027] ;

[0028] In the formula Indicates the patient's body thickness data, Indicates the device's vertical scanning range data. represents the maximum value function, Indicates the scan range match index.

[0029] Optionally, the specific evaluation steps of the device operation evaluation module include:

[0030] Obtain imaging equipment operation data and equipment operation environment data;

[0031] The equipment operation stability index is calculated by the imaging equipment operation data and the equipment operation environment data. The equipment operation stability index is used to quantify the operation stability of the imaging equipment. The calculation formula of the equipment operation stability index is:

[0032] ;

[0033] In the formula express Moment The operating parameter values ​​of each type of equipment, express Moment The operating parameter values ​​of each type of equipment, represents the medical image scanning time, Indicates the number of device operation parameter types. express Moment The operating environment parameter values ​​of each type of equipment, express Moment The operating environment parameter values ​​of each type of equipment, Indicates the number of device operating environment parameter types. represents the adjustment factor, Indicates the equipment operation stability index.

[0034] Optionally, the specific estimation steps of the imaging quality estimation module include:

[0035] Obtain body position jitter index, scanning range matching index and equipment operation stability index;

[0036] The medical imaging quality index is calculated by the body position jitter index, scanning range matching index and equipment operation stability index. The medical imaging quality index is used to estimate the medical imaging effect. The calculation formula of the medical imaging quality index is:

[0037] ;

[0038] In the formula It represents the body position jitter index. Indicates the scan range matching index, Indicates the equipment operation stability index. represents the body position jitter weight, Indicates the scan range matching weight, Indicates the weight of equipment operation stability. Represents the medical imaging quality index;

[0039] When the medical image imaging quality index is less than the preset medical image imaging quality threshold, a medical image imaging quality unqualified warning is issued; when the medical image imaging quality index is greater than or equal to the preset medical image imaging quality threshold, no medical image imaging quality warning is issued and the medical image is output.

[0040] It should be noted here that the jitter displacement weight, jitter speed weight, jitter angular velocity weight, adjustment factor, body position jitter weight, scanning range matching weight and equipment operation stability weight are taken as follows: 5000 sets of patient body position image sequences, imaging device operation data, equipment operation environment data and patient body thickness data are collected to distinguish whether the medical imaging quality meets the imaging requirements, and the patient body position image sequences, imaging device operation data, equipment operation environment data and patient body thickness data are substituted into the medical imaging quality index calculation formula for calculation, and the calculated medical imaging quality index and the distinction result are simultaneously imported into the fitting software, and the optimal jitter displacement weight, jitter speed weight, jitter angular velocity weight, adjustment factor, body position jitter weight, scanning range matching weight and equipment operation stability weight that meet the distinction accuracy of the distinction result are output.

[0041] In a second aspect, the present application provides an intelligent clustering analysis method based on feature extraction, comprising:

[0042] Collect patient position image sequences, imaging equipment operation data, equipment operation environment data, and patient body thickness data during medical imaging scanning;

[0043] The degree of patient position jitter is obtained by performing image registration on the acquired patient position image sequence and analyzing the registered patient position image sequence;

[0044] By analyzing the patient's body thickness data and the imaging device's operating data, the matching degree of the scanning range is obtained;

[0045] By analyzing the imaging equipment operation data and equipment operation environment data, the operation stability of the imaging equipment is obtained;

[0046] The quality of medical imaging can be estimated by analyzing the degree of body position jitter, scanning range matching and operating stability of imaging equipment.

[0047] In a third aspect, the present application provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a method for intelligent medical image evaluation by calling the computer program stored in the memory.

[0048] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute a method for intelligent medical image evaluation.

[0049] Compared with the prior art, this application has the following advantages and beneficial effects:

[0050] The present application performs image registration on the collected patient position image sequence through the image registration module, analyzes the registered patient position image sequence through the position jitter assessment module to evaluate the patient's position jitter degree, analyzes the patient's body thickness data and imaging device operation data through the scanning range assessment module to evaluate the scanning range matching degree, analyzes the imaging device operation data and the device operation environment data through the equipment operation assessment module to evaluate the imaging device operation stability, and finally, comprehensively analyzes the position jitter degree, scanning range matching degree and imaging device operation stability through the imaging quality estimation module, thereby estimating the imaging quality of medical images, thereby improving the accuracy and reliability of medical image quality assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0052] Figure 1 It is a structural schematic diagram of a medical image intelligent film evaluation system provided in an embodiment of the present application;

[0053] Figure 2 is a schematic diagram of a feature-based image registration process provided in an embodiment of the present application;

[0054] Figure 3 It is a flowchart of a medical image intelligent evaluation method provided by an embodiment of the present application;

[0055] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0057] See also Figure 1 , Figure 1 1 is a schematic diagram of the structure of a medical image intelligent evaluation system provided in an embodiment of the present application, comprising a data acquisition module 110, an image registration module 120, a body position jitter evaluation module 130, a scanning range evaluation module 140, an equipment operation evaluation module 150 and an imaging quality estimation module 160;

[0058] The data acquisition module 110 is used to acquire the patient's body position image sequence, imaging equipment operation data and equipment operation environment data during the medical imaging scanning process, and also to acquire the patient's body thickness data;

[0059] The image registration module 120 is used to perform image registration on the acquired patient body position image sequence, and send the registered patient body position image sequence to the body position jitter assessment module;

[0060] The body position jitter assessment module 130 is used to analyze the registered patient body position image sequence to obtain the patient's body position jitter degree;

[0061] The scanning range evaluation module 140 is used to analyze the patient's body thickness data and the imaging device operation data to obtain the scanning range matching degree;

[0062] The device operation evaluation module 150 is used to analyze the imaging device operation data and the device operation environment data to obtain the imaging device operation stability;

[0063] The imaging quality estimation module 160 is used to analyze the degree of body position jitter, the degree of scanning range matching and the operating stability of the imaging device, and to estimate the imaging quality of the medical image.

[0064] In the embodiment of the present application, the image registration module 120 is used to perform image registration on the collected patient position image sequence, and send the registered patient position image sequence to the position jitter assessment module, wherein the image sequence is used to capture and record the process of movement or change. By processing and analyzing the image sequence, a deeper understanding and insight into the law of movement or change can be obtained. In the fields of computer vision and image processing, image sequences are widely used in motion analysis and target tracking. The patient position image sequence refers to a collection of a series of patient position images arranged in chronological order. Each patient position image represents the body position state of the patient at a certain moment, and image registration (ImageRegistration) is used to align multiple images. In the embodiment of the present application, a feature-based image registration method is used to register the collected patient position image sequence. Please refer to Figure 2 , Figure 2 It is a schematic diagram of the feature-based image registration process provided in an embodiment of the present application, which mainly includes the following steps: first, obtain the images to be registered, preprocess both to remove noise or enhance features, extract significant feature points such as corners, edges, etc. from the two images, then perform feature matching on the extracted features, find potential matching pairs through a similarity measurement method, further screen the optimal matching points to eliminate false matches, and estimate the transformation model (such as affine, perspective, etc.) based on the optimal matching point pairs, and perform a geometric transformation on the image to be registered based on the estimated transformation model. Finally, generate a registered image aligned with the reference image to achieve spatial alignment of the two images. The advantage of the feature-based image registration method is that it has good robustness to image rotation, scaling and brightness changes, and is particularly suitable for processing small-amplitude translation registration under the same modality.

[0065] In the embodiment of the present application, the body position jitter assessment module 130 is used to analyze the registered patient body position image sequence to obtain the patient's body position jitter degree. The specific assessment steps of the body position jitter assessment module include:

[0066] Acquire a registered patient position image sequence;

[0067] Extracting jitter data in the patient's body position images at adjacent acquisition moments through the patient's body position image sequence, the jitter data including jitter displacement, jitter velocity and jitter angular velocity;

[0068] The body position jitter index is calculated based on the patient's jitter data. The body position jitter index is used to quantify the patient's body position jitter degree. The calculation formula of the body position jitter index is:

[0069] ;

[0070] In the formula express The jitter displacement at the moment, represents the mean jitter displacement of the patient during the medical imaging scan. , represents the medical image scanning time, express The jitter speed of the moment, represents the mean shaking speed of the patient during the medical imaging scan. , express The angular velocity of the vibration at the moment, represents the mean angular velocity of the patient's jitter during medical imaging scanning, Used to quantify the degree of change in jitter direction, , represents the jitter displacement weight, represents the jitter speed weight, represents the jitter angular velocity weight, It represents the body position jitter index;

[0071] Jitter data is used to quantify the patient's body position jitter during the medical imaging process. The greater the jitter, the more details of the medical image may be lost due to blurring or ghosting, affecting the clarity of the image and the accuracy of subsequent diagnosis. Evaluating jitter data helps to estimate and judge the blurriness of medical images and extract jitter data from patient body position images at adjacent acquisition moments, including:

[0072] Acquire patient position image sequence Patient position image at any time and Patient position image at any time ;

[0073] Patient position image and patient position images Calculate the patient jitter data. The calculation formula for the patient jitter data is:

[0074] ;

[0075] In the formula Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Represents the number of pixels in the patient position image, express The jitter displacement at the moment, Indicates the time interval between adjacent collection times, express The jitter speed of the moment, Indicates Pixels in The jitter angle at the moment, Indicates Pixels in The jitter angle at the moment, express The jitter angular velocity at the moment.

[0076] In the embodiment of the present application, the scanning range evaluation module 140 is used to analyze the patient's body thickness data and the imaging device operation data to obtain the scanning range matching degree. The scanning range matching index is used to quantify the matching degree between the longitudinal scanning range of the imaging device and the patient's body thickness, so as to evaluate the influence of the scanning range on the imaging quality. When the scanning range is insufficient, part of the anatomical structure may be truncated or not covered, affecting the integrity and accuracy of the diagnosis. If the scanning range is too large, it will cause unnecessary radiation exposure and increase the risk of the patient. The specific evaluation steps of the scanning range evaluation module include:

[0077] Obtain the patient's body thickness data and the longitudinal scanning range data of the imaging device in the operating data. The patient's body thickness data refers to the measurement data used to describe the patient's body thickness in medical imaging. It is usually measured directly at the maximum thickness of the corresponding part of the body using a tape measure or a soft ruler. The longitudinal scanning range data of the device refers to the longitudinal distance that the medical imaging device can cover during a single scan. It is obtained from the product manual of the medical imaging device.

[0078] The scanning range matching index is calculated by using the patient's body thickness data and the longitudinal scanning range data. The scanning range matching index is used to quantify the matching degree between the longitudinal scanning range of the imaging device and the patient's body thickness. The calculation formula of the scanning range matching index is:

[0079] ;

[0080] In the formula Indicates the patient's body thickness data, Indicates the device's vertical scanning range data. represents the maximum value function, Indicates the scan range matching index. hour, , indicating that the longitudinal scanning range of the device completely covers the patient's body thickness, that is, the matching degree is the best. hour, , indicating that the scan range coverage is insufficient, that is, the matching degree is reduced.

[0081] In the embodiment of the present application, the device operation evaluation module 150 is used to analyze the imaging device operation data and the device operation environment data to obtain the imaging device operation stability. The specific evaluation steps of the device operation evaluation module include:

[0082] Obtain imaging equipment operation data and equipment operation environment data;

[0083] The equipment operation stability index is calculated by the imaging equipment operation data and the equipment operation environment data. The equipment operation stability index is used to quantify the operation stability of the imaging equipment. The calculation formula of the equipment operation stability index is:

[0084] ;

[0085] In the formula express Moment The operating parameter values ​​of each type of equipment, express Moment The equipment operating parameter values ​​of each type include tube voltage, tube current, magnetic field strength and radiation dose. represents the medical image scanning time, Indicates the number of device operation parameter types. express Moment The equipment operating environment parameters include ambient temperature, ambient humidity, ambient electromagnetic interference intensity and ambient cleanliness. express Moment The operating environment parameter values ​​of each type of equipment, Indicates the number of device operating environment parameter types. represents the adjustment factor, Indicates the equipment operation stability index.

[0086] In the embodiment of the present application, the imaging quality estimation module 160 is used to analyze the degree of body position jitter, the degree of scanning range matching and the operating stability of the imaging device, estimate the imaging quality of medical images, and estimate the imaging effect of medical images by calculating the imaging quality index of medical images. It can detect possible medical image quality problems in advance, reduce repeated scanning caused by image blur, insufficient coverage of the target area, etc. after imaging, and reduce unnecessary radiation dose and scanning time for patients. The specific estimation steps of the imaging quality estimation module include:

[0087] Obtain body position jitter index, scanning range matching index and equipment operation stability index;

[0088] The medical imaging quality index is calculated by the body position jitter index, scanning range matching index and equipment operation stability index. The medical imaging quality index is used to estimate the medical imaging effect. The calculation formula of the medical imaging quality index is:

[0089] ;

[0090] In the formula Represents the body jitter index, Indicates the scan range matching index, Indicates the equipment operation stability index. represents the body position jitter weight, Indicates the scan range matching weight, Indicates the weight of equipment operation stability. Represents the medical imaging quality index;

[0091] When the medical image imaging quality index is less than the preset medical image imaging quality threshold, a medical image imaging quality unqualified warning is issued; when the medical image imaging quality index is greater than or equal to the preset medical image imaging quality threshold, no medical image imaging quality warning is issued and the medical image is output.

[0092] See also Figure 3 , Figure 3 This is a flowchart of a medical image intelligent evaluation method provided by an embodiment of the present application, which specifically includes the following steps:

[0093] S210: collecting a patient's body position image sequence, imaging device operation data, and device operation environment data during the medical imaging scanning process, and collecting the patient's body thickness data;

[0094] S220: Obtaining the degree of body position jitter of the patient by performing image registration on the acquired patient body position image sequence and analyzing the registered patient body position image sequence;

[0095] The specific evaluation steps of the body jitter evaluation module include:

[0096] Acquire a registered patient position image sequence;

[0097] Extracting jitter data in the patient's body position images at adjacent acquisition moments through the patient's body position image sequence, the jitter data including jitter displacement, jitter velocity and jitter angular velocity;

[0098] The body position jitter index is calculated based on the patient's jitter data. The body position jitter index is used to quantify the patient's body position jitter degree. The calculation formula of the body position jitter index is:

[0099] ;

[0100] In the formula express The jitter displacement at the moment, represents the mean jitter displacement of the patient during the medical imaging scan. represents the medical image scanning time, express The jitter speed of the moment, represents the mean shaking speed of the patient during the medical imaging scan. express The angular velocity of the vibration at the moment, represents the mean angular velocity of the patient's jitter during medical imaging scanning, represents the jitter displacement weight, represents the jitter speed weight, represents the jitter angular velocity weight, It represents the body position jitter index;

[0101] Extract jitter data from patient position images at adjacent acquisition moments, including:

[0102] Acquire patient position image sequence Patient position image at any time and Patient position image at any time ;

[0103] Patient position image and patient position images Calculate the patient jitter data. The calculation formula for the patient jitter data is:

[0104] ;

[0105] In the formula Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Represents the number of pixels in the patient position image, express The jitter displacement at the moment, Indicates the time interval between adjacent collection times, express The jitter speed of the moment, Indicates Pixels in The jitter angle at the moment, Indicates Pixels in The jitter angle at the moment, express The jitter angular velocity at the moment.

[0106] S230: Obtaining a scanning range matching degree by analyzing the patient's body thickness data and the imaging device operation data;

[0107] The specific evaluation steps of the scanning range assessment module include:

[0108] Acquire patient body thickness data and device longitudinal scanning range data from imaging device operation data;

[0109] The scanning range matching index is calculated by using the patient's body thickness data and the longitudinal scanning range data. The scanning range matching index is used to quantify the matching degree between the longitudinal scanning range of the imaging device and the patient's body thickness. The calculation formula of the scanning range matching index is:

[0110] ;

[0111] In the formula Indicates the patient's body thickness data, Indicates the device's vertical scanning range data. represents the maximum value function, Indicates the scan range match index.

[0112] S240: Obtaining imaging device operation stability by analyzing imaging device operation data and device operation environment data;

[0113] The specific evaluation steps of the equipment operation evaluation module include:

[0114] Obtain imaging equipment operation data and equipment operation environment data;

[0115] The equipment operation stability index is calculated by the imaging equipment operation data and the equipment operation environment data. The equipment operation stability index is used to quantify the operation stability of the imaging equipment. The calculation formula of the equipment operation stability index is:

[0116] ;

[0117] In the formula express Moment The operating parameter values ​​of each type of equipment, express Moment The operating parameter values ​​of each type of equipment, represents the medical image scanning time, Indicates the number of device operation parameter types. express Moment The operating environment parameter values ​​of each type of equipment, express Moment The operating environment parameter values ​​of each type of equipment, Indicates the number of device operating environment parameter types. represents the adjustment factor, Indicates the equipment operation stability index.

[0118] S250: Estimate the quality of medical imaging by analyzing the degree of body position jitter, scanning range matching and imaging equipment operation stability;

[0119] The specific estimation steps of the imaging quality estimation module include:

[0120] Obtain body position jitter index, scanning range matching index and equipment operation stability index;

[0121] The medical imaging quality index is calculated by the body position jitter index, scanning range matching index and equipment operation stability index. The medical imaging quality index is used to estimate the medical imaging effect. The calculation formula of the medical imaging quality index is:

[0122] ;

[0123] In the formula It represents the body position jitter index. Indicates the scan range matching index, Indicates the equipment operation stability index. represents the body position jitter weight, Indicates the scan range matching weight, Indicates the weight of equipment operation stability. Represents the medical imaging quality index;

[0124] When the medical image imaging quality index is less than the preset medical image imaging quality threshold, a medical image imaging quality warning is issued; when the medical image imaging quality index is greater than or equal to the preset medical image imaging quality threshold, no medical image imaging quality warning is issued.

[0125] The above parameters and steps in the medical image intelligent evaluation method of the present application can refer to the parameters and steps of each unit module to implement the corresponding functions in the embodiment of a medical image intelligent evaluation system above, and will not be repeated here.

[0126] See also Figure 4 The embodiment of the present invention further provides an electronic device 300, including a memory 310, a processor 320 and a communication bus 330; the memory 310 and the processor 320 are connected via the communication bus 330. The memory 310 stores a medical image intelligent evaluation method provided in the above embodiment that can be loaded and executed by the processor 320.

[0127] The memory 310 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 310 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing a medical image intelligent film evaluation method provided in the above embodiment, etc.; the data storage area may store data involved in a medical image intelligent film evaluation method provided in the above embodiment, etc.

[0128] The processor 320 may include one or more processing cores. The processor 320 executes various functions and processes data of the present application by running or executing instructions, programs, code sets or instruction sets stored in the memory 310, calling the data stored in the memory 310. The processor 320 may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller and a microprocessor. It can be understood that for different devices, the electronic device used to implement the above-mentioned processor 320 function can also be other, and the embodiment of the present application is not specifically limited.

[0129] The communication bus 330 may include a path to transmit information between the above components. The communication bus 330 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The communication bus 330 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one double arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0130] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute a medical image intelligent evaluation method as provided in the above embodiment.

[0131] In an embodiment of the present application, a computer-readable storage medium may be a tangible device that holds and stores instructions used by an instruction execution device. A computer-readable storage medium may be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, a computer-readable storage medium may be a portable computer disk, a hard disk, a USB flash drive, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a podium random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, an optical disk, a magnetic disk, a mechanical encoding device, and any combination thereof.

[0132] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or also includes elements inherent to such process, method, article, or apparatus.

[0133] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned application concept. For example, the above features are replaced with (but not limited to) technical features with similar functions applied in the present application.

Claims

1. A medical image intelligent film evaluation system, characterized in that: It includes data acquisition module, image registration module, body position jitter assessment module, scanning range assessment module, equipment operation assessment module and imaging quality estimation module; The data acquisition module is used to acquire the patient's body position image sequence, imaging equipment operation data and equipment operation environment data during the medical imaging scanning process, and to acquire the patient's body thickness data; The image registration module is used to perform image registration on the acquired patient body position image sequence, and send the registered patient body position image sequence to the body position jitter assessment module; The body position jitter assessment module is used to analyze the registered patient body position image sequence to obtain the patient's body position jitter degree; The scanning range evaluation module is used to analyze the patient's body thickness data and the imaging device operation data to obtain the scanning range matching degree; The equipment operation evaluation module is used to analyze the imaging equipment operation data and the equipment operation environment data to obtain the imaging equipment operation stability; The imaging quality estimation module is used to analyze the degree of body position jitter, the degree of scanning range matching and the operating stability of the imaging device to estimate the imaging quality of the medical image; The specific evaluation steps of the body position jitter evaluation module include: Acquire a registered patient position image sequence; Extracting jitter data in the patient's body position images at adjacent acquisition moments through the patient's body position image sequence, the jitter data including jitter displacement, jitter velocity and jitter angular velocity; The body position jitter index is calculated based on the patient's jitter data. The body position jitter index is used to quantify the patient's body position jitter degree. The calculation formula of the body position jitter index is: ； In the formula express The jitter displacement at the moment, represents the mean jitter displacement of the patient during the medical imaging scan. represents the medical image scanning time, express The jitter speed of the moment, represents the mean shaking speed of the patient during the medical imaging scan. express The jitter angular velocity at the moment, represents the mean angular velocity of the patient's jitter during medical imaging scanning, represents the jitter displacement weight, represents the jitter speed weight, represents the jitter angular velocity weight, It represents the body position jitter index; The specific estimation steps of the imaging quality estimation module include: Obtain body position jitter index, scanning range matching index and equipment operation stability index; The medical imaging quality index is calculated by the body position jitter index, scanning range matching index and equipment operation stability index. The medical imaging quality index is used to estimate the medical imaging effect. The calculation formula of the medical imaging quality index is: ； In the formula It represents the body position jitter index. Indicates the scan range matching index, Indicates the equipment operation stability index. represents the body position jitter weight, Indicates the scan range matching weight, Indicates the weight of equipment operation stability. Represents the medical imaging quality index; When the medical image imaging quality index is less than a preset medical image imaging quality threshold, a medical image imaging quality warning is issued.

2. The medical image intelligent evaluation system according to claim 1, characterized in that: The step of extracting jitter data from patient body position images at adjacent acquisition moments comprises: Acquire patient position image sequence Patient position image at any time and Patient position image at any time ; Patient position image and patient position images Calculate the patient jitter data. The calculation formula for the patient jitter data is: ； In the formula Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Indicates pixels in the patient position image The horizontal axis in Indicates pixels in the patient position image The vertical coordinate in Represents the number of pixels in the patient position image, express The jitter displacement at the moment, Indicates the time interval between adjacent collection times, express The jitter speed of the moment, Indicates Pixels in The jitter angle at the moment, Indicates Pixels in The jitter angle at the moment, express The jitter angular velocity at the moment.

3. The intelligent medical image evaluation system according to claim 1, characterized in that: The specific evaluation steps of the scanning range evaluation module include: Acquire patient body thickness data and device longitudinal scanning range data from imaging device operation data; The scanning range matching index is calculated by using the patient's body thickness data and the longitudinal scanning range data. The scanning range matching index is used to quantify the matching degree between the longitudinal scanning range of the imaging device and the patient's body thickness. The calculation formula of the scanning range matching index is: ； In the formula Indicates the patient's body thickness data, Indicates the device's vertical scanning range data. represents the maximum value function, Indicates the scan range match index.

4. The medical image intelligent evaluation system according to claim 1, characterized in that: The specific evaluation steps of the equipment operation evaluation module include: Obtain imaging equipment operation data and equipment operation environment data; The equipment operation stability index is calculated by the imaging equipment operation data and the equipment operation environment data. The equipment operation stability index is used to quantify the operation stability of the imaging equipment. The calculation formula of the equipment operation stability index is: ； In the formula express Moment The operating parameter values ​​of each type of equipment, express Moment The operating parameter values ​​of each type of equipment, represents the medical image scanning time, Indicates the number of device operation parameter types. express Moment The operating environment parameter values ​​of each type of equipment, express Moment The operating environment parameter values ​​of each type of equipment, Indicates the number of device operating environment parameter types. represents the adjustment factor, Indicates the equipment operation stability index.

5. A medical image intelligent evaluation method, applied to a medical image intelligent evaluation system according to any one of claims 1 to 4, characterized in that: The method comprises: Collect patient position image sequences, imaging equipment operation data, equipment operation environment data, and patient body thickness data during medical imaging scanning; The degree of patient position jitter is obtained by performing image registration on the acquired patient position image sequence and analyzing the registered patient position image sequence; By analyzing the patient's body thickness data and the imaging device operation data, the matching degree of the scanning range is obtained; By analyzing the imaging equipment operation data and equipment operation environment data, the operation stability of the imaging equipment is obtained; The quality of medical imaging can be estimated by analyzing the degree of body position jitter, scanning range matching and operating stability of imaging equipment.

6. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes a medical image intelligent evaluation method as described in claim 5 by calling the computer program stored in the memory.

7. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes the medical image intelligent evaluation method as claimed in claim 5.

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