Abstract
With the development of digital image technology, judging diseases by medical image plays an important role in medical diagnosis. Mammography is the most effective imaging examination method for breast cancer at present. Intelligent segmentation and identification of breast cancer images and judging their size and classification by digital image processing technology can promote the development of clinical medicine. This paper introduces the preprocessing technology of breast cancer pathological image and medical image recognition technology of breast cancer. In order to improve the segmentation accuracy of image processing and optimize, the segmentation recognition ability in digital mammography was improved. Based on the technical basis of pathological image analysis of breast cancer, the architecture of intelligent segmentation and recognition system for breast cancer was constructed, and each functional module of intelligent system was introduced in detail. Based on digital image processing technology, filtering technology is used to reduce dryness and improve the clarity of the image. Public datasets INBreast and DDSM-BCRP were used to verify system’s performance, and it was tested on the breast cancer image test set. The experiment shows that the comprehensive performance of the intelligent segmentation and recognition system can realize the segmentation and recognition of breast cancer and has higher accuracy and interpretability, which is helpful to improve the diagnosis of doctors.
Highlights
With the development of medical and health services, the digital application of pathological samples has become more and more wide in large hospitals equipped with pathological full-section scanning equipment, and the intelligent segmentation recognition and detection of digital pathological images has gradually become one of the research hotspots in the field of modern medical images [1]
With the development of digital image technology, judging diseases by medical image plays an important role in medical diagnosis
Using digital image processing technology to segment and recognize breast cancer images intelligently, judging their general position, size, and classification can promote the development of clinical medicine
Summary
With the development of medical and health services, the digital application of pathological samples has become more and more wide in large hospitals equipped with pathological full-section scanning equipment, and the intelligent segmentation recognition and detection of digital pathological images has gradually become one of the research hotspots in the field of modern medical images [1]. The detection and recognition of pathological sections of breast cancer by ARTIFICIAL intelligence can provide medical personnel with accurate data of lesion areas or areas of interest, which is of far-reaching significance to improve the utilization value of medical images and greatly help to improve the accuracy and rapidity of pathological diagnosis [4]. It is necessary to ensure that the segmented image has a high consistency, and the picture cannot be substantially changed
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