Abstract：The image of histological sections is important for cancer diagnosis and has been widely used in the medical work and
scientific research. The traditional techniques of histological sections cancer diagnosis mainly rely on the personal experience of
the doctor, which is time-consuming, and the results of the diagnosis are easy to be biased. In this paper, we proposed a recognition
method of breast section cancer cells based on the computer pattern recognition technologies. This method can effectively fuse
a variety of feature information of breast section cell image and combine the decision of the multiple classifiers to improve the
accuracy of breast cancer cells recognition.
刘景鑫1，张同舟2，郑彩侠2，张磊超1，徐慧2，孔俊2. 基于双层信息融合的乳腺切片癌细胞识别[J]. 中国医疗设备, 2018, 33(1): 20-23.
LIU Jingxin1, ZHANG Tongzhou2, ZHENG Caixia2, ZHANG Leichao1, XU Hui2, KONG Jun2. Recognition of Breast Section Cancer Cells Based on Double-Layer Information Fusion. China Medical Devices, 2018, 33(1): 20-23.