Mammary gland X-ray image quality evaluation system and method

Abstract

The invention discloses a mammary gland X-ray image quality evaluation system and a mammary gland X-ray image quality evaluation method. The evaluation system comprises an acquisition module, a quality evaluation module and an evaluation result display module. The acquisition module is used for acquiring a to-be-detected mammary gland X-ray video through a workstation and sending the to-be-detected mammary gland X-ray video to the quality evaluation module; the quality evaluation module is used for carrying out quality evaluation on the mammary gland X-ray video to be detected to obtain an evaluation result; the evaluation result display module is used for receiving the evaluation result of the quality evaluation module and displaying the evaluation result through an all-in-one machine; therefore, automatic quality detection of the mammary gland X-ray image can be achieved, the accuracy of mammary gland X-ray image quality detection is improved, instant feedback can be provided for technicians to shoot the image, and then qualified images are provided for doctors to diagnose.

Description

technical field [0001] The invention belongs to the technical field of medical imaging, and in particular relates to a system and method for evaluating mammography image quality. Background technique [0002] Mammography diagnosis is firstly performed by the imaging technician to take X-ray images of the patient's breasts, and then by the reading doctor to analyze and diagnose the mammography images. The quality of mammography images has a significant impact on diagnosis. Mammography images with better quality can penetrate the glands and can easily identify lesions in the glands; It will increase the difficulty of diagnosis for the doctor who reads the film, making the lesions difficult to identify. At present, there are three common quality control schemes: 1. The chief technician or clinical diagnosis doctor of the hospital visits the mammography room for spot checks, points out the irregularity and unqualified shooting, and gives shooting suggestions; 2. The technician ...

AI Technical Summary

Problems solved by technology

[0003] However, the current common quality control scheme has the following defects: the chief technician and the diagnostician are limited by the cognitive level, and there are limitations and randomness in the control of image quality; and the chief technician and the diagnostician cannot always give guidance between shootings

There is a problem of timeliness when the technician shoots the image and pushes it to the diagnostician or the superior hospital, and it is impossible to evaluate the image quality immediately after shooting

For example: In the case of unqualified and irregular shooting, it is easy to miss the time for reshooting because it cannot be evaluated immediately

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