Computer aided method of predicting mammary cancer risk

Abstract

The computer aided method of predicting mammary cancer risk includes the following steps: partitioning the mammary gland tissue area in X-ray image regularly into small areas and calculating the density characteristic value of the small areas; selecting the initial suspicious small areas with the preset density characteristic value for further research; judging the final suspicious small areas based on the information in the corresponding areas and the adjacent areas on two frames of images; and judging the near term mammary cancer risk of the testee based on the existence of the marked final suspicious small areas and predicting the mammary cancer position in case of existing final suspicious small areas. The present invention has high objectivity, high accuracy and high effectiveness in predicting mammary cancer risk.

Description

technical field [0001] The invention belongs to the application field of computer analysis technology of medical images, and in particular relates to a method for computer-aided prediction of breast cancer risk. Background technique [0002] Breast cancer is one of the leading causes of death among women over 50 years old in developed countries such as Europe and America. The incidence of breast cancer among women in my country, especially in large and medium-sized cities, is increasing year by year. Studies have shown that early diagnosis and treatment of breast cancer can greatly reduce the mortality of patients. For the early diagnosis of breast cancer, mammography is considered to be the most reliable and effective method at present. In developed countries such as Europe and the United States, women aged 40 and above undergo mammogram screening every year. In 2003, my country began to implement the "Million Women's Breast Screening Project", which fully shows that the...

AI Technical Summary

Problems solved by technology

[0004] At present, most of the research on breast cancer risk in the world is based on the density analysis of a single image, such as the two patents of the US Patent Application No. The disadvantage of prediction is that it is possible to mistake local high-density areas of normal tissue on a single image as breast cancer risk areas for false positives

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