Quality control method and system for intra-frame weighted medical image with similar specific attention

By employing an intra-frame weighted medical image quality control method, the problem of weak discrimination capability in 3D medical image processing is solved, the sensitivity to subtle artifacts and positional deviations is improved, multi-dimensional and precise image quality control is achieved, and the quality control efficiency and equipment adaptability are enhanced.

CN120953289AActive Publication Date: 2025-11-14安徽影联云享医疗科技有限公司
4 Cites 1 Cited by

Patent Information

Application Number
CN202511484979.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-17
Publication Date
2025-11-14
Estimated Expiration
2045-10-17

AI Technical Summary

Technical Problem

Existing medical image processing methods have weak discrimination capabilities when dealing with 3D medical images, and are less sensitive to subtle artifacts and positional deviations, resulting in weak recognition capabilities.

Method used

A neural network-based intra-frame weighted medical image quality control method is adopted. Through data preprocessing, spatial feature extraction, temporal enhancement feature extraction, category-guided intra-frame weighted score calculation and model optimization, class activation maps are generated to focus on key anatomical regions and improve the model's sensitivity to subtle artifacts and positional deviations.

Benefits of technology

It enables multi-dimensional, precise, and real-time quality assessment of 3D medical images, improves quality control efficiency, reduces duplicate scanning rates, and is adaptable to various image types and devices.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses a quality control method and system for an intra-frame weighted medical image with similar specific attention, relates to the technical field of medical images, and solves the technical problems that when an existing medical image processing method is used for processing a 3D medical image, the discrimination capability is weak, and the sensitivity to subtle artifacts or body position deviation is low, so that the recognition capability is weak. Comprising the steps that medical image data are acquired, and the medical image data comprise a 3D medical image and an evaluation system corresponding to the 3D medical image; performing data labeling on the 3D medical image based on an evaluation system to obtain a plurality of sequence data; dividing the plurality of sequence data into a training set, a verification set and a test set; training the medical image quality control model based on the training set, the verification set and the test set; the training process comprises data preprocessing, spatial feature extraction, time sequence enhancement feature extraction, class-guided intra-frame weighted score calculation, model optimization and class activation graph generation; and the model identification capability is enhanced.
Need to check novelty before this filing date? Find Prior Art