#Breast calcification clusters how to

#Breast calcification clusters how to

How to classify clustered calcifications comes to be an important breakthrough in controlling breast cancer. The appearance of clustered calcifications is one of the important signs of breast cancer ( 5), and the high correlation between clustered calcifications and breast cancer has also attracted extensive attention in medical communities and academic circles. At present, as a relatively low-dose, safe, and low-cost means of image detection, all-digital mammography has become one of the best methods for routine clinical examination and preventive screening of breast cancer ( 3, 4). Therefore, early diagnosis and early treatment are particularly important for women with breast cancer. However, there is still a lack of detailed scientific understanding of the causes and mechanisms of breast cancer, and thus it is particularly difficult to prevent breast cancer ( 2). According to the statistics of the World Health Organization, in 2020, there were 2.3 million new cases of breast cancer among women worldwide, and about 685,000 women died of breast cancer, accounting for 15.5% of all female deaths from malignant tumor ( 1).

The results show that the performance of the fusion model proposed in this paper is obviously superior to that of the two classification models in the classification of clustered microcalcification.īreast cancer is one of the diseases with the highest incidence and mortality among women in the world. These two models are fused to obtain a complementary model of image information and spatial information. In this study, the discriminant model based on image convolution is used to learn the image features related to the classification of clustered microcalcifications, and the graph convolutional network (GCN) based on topological graph is used to learn the spatial distribution characteristics of clustered microcalcifications. The appearance of clustered calcifications is one of the important signs of breast cancer, and thus how to classify clustered calcifications comes to be a key breakthrough in controlling breast cancer. 4School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, Chinaīreast cancer is one of the diseases with the highest incidence and mortality among women in the world, which has posed a serious threat to women’s health.3Department of Radiology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.2Department of Clinical Laboratory, Children’s Hospital of Nanjing Medical University, Nanjing, China.1Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China.Yaqin Zhang 1, Jiayue Han 1, Binghui Chen 1, Lin Chang 2*, Ting Song 3* and Guanxiong Cai 4*