Machine Learning Techniques for Challenging Tumor Detection and Classification in Breast Cancer
Afsaneh Jalalian, Babak Karasfi · 2018
Breast cancer is the foremost common invasive cancer among ladies and is the primary cause of mortality from cancer around the world. To avoid the tall mortality, early detection and treatment are essential. Breast screening which uses noninvasive manner to assess tissue properties plays an imperative role in early designation. In any case, the huge information volume makes the examination become long, time-consuming and inoperable. Machine learning techniques and image processing are trending to investigate different tissue characterization and tumor appearance in radiology for automatic malignancy classification. This paper provide comparison of two supervised classification techniques for angiogenesis detection in computed tomography laser mammography image which is the major sign of high hemoglobin concentration and breast cancer.