CN-115206499-B - Image processing method, device, system and electronic device

CN115206499BCN 115206499 BCN115206499 BCN 115206499BCN-115206499-B

Abstract

The application relates to an image processing method, an image processing device, an image processing system and an electronic device, wherein the image processing method comprises the steps of obtaining a medical image to be processed and a first configuration parameter corresponding to the medical image to be processed, matching the first configuration parameter with a second configuration parameter corresponding to a die body image in a preset configuration file, wherein the configuration file comprises at least one second configuration parameter corresponding to the die body image and a target filter parameter for carrying out post-processing on each die body image, and carrying out image processing on the medical image to be processed according to the corresponding target filter parameter under the condition that matching is successful, so as to generate an image processing result. The application solves the problem of low image processing efficiency, and realizes the PET quantitative analysis method with high intelligent degree and multiple centers.

Inventors

MA RUNXIA
JI ZIJUN
LI JINGJING
LV YANG

Assignees

上海联影医疗科技股份有限公司

Dates

Publication Date: 20260505
Application Date: 20220727

Claims (8)

1. A positron emission computed tomography image processing method, wherein the method is applied to an intelligent image processing software tool deployed on a terminal device, the method comprising: Acquiring a medical image to be processed and first configuration parameters corresponding to the medical image to be processed, and matching the first configuration parameters with second configuration parameters corresponding to die body images in a preset configuration file, wherein the configuration file comprises at least one second configuration parameter corresponding to the die body images and target filter parameters for post-processing each die body image; under the condition of successful matching, performing image processing on the medical image to be processed according to the corresponding target filter parameters to generate an image processing result; Performing image processing on the medical image to be processed according to the corresponding target filter parameters, wherein the generating an image processing result comprises the following steps: performing post-processing on the medical image to be processed according to the target filter parameters to obtain a normalized image; calculating the normalized image to obtain a normalized quantitative result, and generating the image processing result based on the normalized quantitative result, wherein the normalized quantitative result comprises a standard uptake value.
2. The positron emission computed tomography image processing method of claim 1, wherein prior to the acquiring of the medical image to be processed, the method further comprises: acquiring a preset data analysis standard and the die body image; filtering the die body image to obtain a processed die body image, calculating the processed die body image to obtain an image recovery coefficient, and determining the target filter parameter according to a comparison result of the image recovery coefficient and the data analysis standard; And acquiring the second configuration parameters corresponding to the die body image, and generating the configuration file according to the target filter parameters and the second configuration parameters.
3. The positron emission computed tomography image processing method of claim 2, wherein the calculating the processed phantom image to obtain an image restoration coefficient and determining the target filter parameter based on a comparison of the image restoration coefficient and the data analysis criteria includes: Calculating the processed die body image to obtain the corresponding image recovery coefficient, and comparing the image recovery coefficient with a standard parameter range of the data analysis standard; Responding to the comparison result to indicate that the image recovery coefficient is positioned in the standard parameter range, obtaining the half-width of the Gaussian function corresponding to the image recovery coefficient, and calculating and generating the target filter parameter based on the half-width; And responding to the comparison result to indicate that the image restoration coefficient is positioned outside the standard parameter range, adjusting the half-width, correspondingly acquiring a new image restoration coefficient based on the adjusted half-width until the new image restoration coefficient is detected to be positioned in the standard parameter range, and calculating and generating the target filter parameter based on the adjusted half-width.
4. A positron emission computed tomography image processing method as claimed in claim 3, wherein after the acquisition of the second configuration parameters corresponding to the phantom image, the method further comprises: generating a visual comparison result according to the comparison result of the image recovery coefficient and the data analysis standard, and generating a visual result at least according to the visual comparison result, the second configuration parameter and the Gaussian function half-width; and sending the visual result to terminal equipment for storage, wherein the terminal equipment responds to the query instruction to display the visual result under the condition of receiving the query instruction.
5. A positron emission computed tomography image processing method, wherein the method is applied to an intelligent image processing software tool deployed on a terminal device, the method comprising: Acquiring a medical image to be processed; Acquiring region-of-interest adjustment information and activity ratio adjustment information of a user for the medical image to be processed, and preprocessing the medical image to be processed according to the region-of-interest adjustment information and the activity ratio adjustment information to obtain a preprocessed medical image and a third configuration parameter corresponding to the preprocessed medical image; Matching the third configuration parameters with second configuration parameters corresponding to die body images in a preset configuration file, wherein the configuration file comprises at least one second configuration parameter corresponding to the die body images and target filter parameters for post-processing each die body image, the second configuration parameters comprise data acquisition parameters and image reconstruction parameters, and the third configuration parameters comprise acquisition condition parameters and image reconstruction parameters; under the condition of successful matching, performing image processing on the preprocessed medical image according to the target filter parameters to obtain a final image processing result; performing image processing on the preprocessed medical image according to the target filter parameters to obtain a final image processing result, wherein the final image processing result comprises: post-processing the preprocessed medical image according to the target filter parameters to obtain a normalized image; calculating the normalized image to obtain a normalized quantitative result, and generating the image processing result based on the normalized quantitative result, wherein the normalized quantitative result comprises a standard uptake value.
6. A positron emission computed tomography image processing device is characterized by comprising an acquisition module, a matching module and a generation module; the acquisition module is used for acquiring a medical image to be processed and a first configuration parameter corresponding to the medical image to be processed; The matching module is used for matching the first configuration parameters with second configuration parameters corresponding to die body images in a preset configuration file, wherein the configuration file comprises at least one second configuration parameter corresponding to the die body images and target filter parameters for carrying out post-processing on each die body image; the generation module is used for carrying out image processing on the medical image to be processed according to the corresponding target filter parameters under the condition that the matching is successful, and generating an image processing result; Performing image processing on the medical image to be processed according to the corresponding target filter parameters, wherein the generating an image processing result comprises the following steps: And carrying out post-processing on the medical image to be processed according to the target filter parameters to obtain a normalized image, calculating the normalized image to obtain a normalized quantitative result, and generating the image processing result based on the normalized quantitative result, wherein the normalized quantitative result comprises a standard uptake value.
7. A positron emission computed tomography image processing system is characterized by comprising a terminal device and a server device; The terminal equipment is used for acquiring a medical image to be processed and sending the medical image to be processed to the server equipment; The server device is adapted to perform the positron emission computed tomography image processing method as claimed in any one of claims 1 to 5 for the medical image to be processed.
8. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the positron emission computed tomography image processing method of any one of claims 1 to 5.

Description

Image processing method, device, system and electronic device Technical Field The present application relates to the field of medical image processing technology, and in particular, to an image processing method, device, system, and electronic device. Background The standard uptake value (standard uptake value, abbreviated as SUV) is used as a semi-quantitative analysis parameter of glycolysis level of tumor tissue in positron emission computed tomography (PET-CT image for short), and is widely used for diagnosis and staging, prognosis judgment and curative effect monitoring of tumors due to simple measurement and convenient use, and has great significance in both routine clinical and multi-center clinical tests. However, due to numerous factors such as manufacturer, model, scanning flow, reconstruction algorithm, difference of scanned objects, etc., the SUV measured values will deviate to different degrees, for example, the same test single scanning raw data is reconstructed by using different image reconstruction parameters, and the SUV values of the same region of interest will be different. In the related art, the normalization calculation mode of the SUV value is generally that an input box is provided at a workstation, an operator inputs corresponding filter parameters, the SUV is recalculated after processing an image loaded by the workstation, however, how the key parameters of the filter parameters are obtained is not supported by a set of software, and currently, the operator performs manual calculation by using Excel and the like, so that the efficiency of processing medical images is low. At present, no effective solution is proposed for the problem of low efficiency of image processing in the related art. Disclosure of Invention The embodiment of the application provides an image processing method, an image processing device, an image processing system and an electronic device, which are used for at least solving the problem of low image processing efficiency in the related art. In a first aspect, an embodiment of the present application provides an image processing method, including: Acquiring a medical image to be processed and first configuration parameters corresponding to the medical image to be processed, and matching the first configuration parameters with second configuration parameters corresponding to die body images in a preset configuration file, wherein the configuration file comprises at least one second configuration parameter corresponding to the die body images and target filter parameters for carrying out post-processing on each die body image; and under the condition that the matching is successful, performing image processing on the medical image to be processed according to the target filter parameters, and generating an image processing result. In some of these embodiments, the first configuration parameters and the second configuration parameters each include data acquisition parameters and image reconstruction parameters. In some of these embodiments, prior to the acquiring the medical image to be processed, the method further comprises: acquiring a preset data analysis standard and the die body image; filtering the die body image to obtain a processed die body image, calculating the processed die body image to obtain an image recovery coefficient, and determining the target filter parameter according to a comparison result of the image recovery coefficient and the data analysis standard; And acquiring the second configuration parameters corresponding to the die body image, and generating the configuration file according to the target filter parameters and the second configuration parameters. In some embodiments, the calculating the processed phantom image to obtain an image restoration coefficient, and determining the target filter parameter according to a comparison result of the image restoration coefficient and the data analysis standard includes: Calculating the processed die body image to obtain the corresponding image recovery coefficient, and comparing the image recovery coefficient with a standard parameter range of the data analysis standard; Responding to the comparison result to indicate that the image recovery coefficient is positioned in the standard parameter range, obtaining the half-width of the Gaussian function corresponding to the image recovery coefficient, and calculating and generating the target filter parameter based on the half-width; And responding to the comparison result to indicate that the image restoration coefficient is positioned outside the standard parameter range, adjusting the half-width, correspondingly acquiring a new image restoration coefficient based on the adjusted half-width until the new image restoration coefficient is detected to be positioned in the standard parameter range, and calculating and generating the target filter parameter based on the adjusted half-width. In some embodiments, after the obtaining the second confi