Split and Merge-Based Breast Cancer Segmentation and Classification
Ichrak Khoulqi, Najlae Idrissi · Advances in library and information science (ALIS) book series · 2019
Breast cancer is the most frequent cancer in morocco with 36.1%. It is the second leading cause of death for women all over the world. The effective way to diagnose and treat breast cancer is the early detection because it increases the success of treatment and the chances of survival. Digitized mammographic images are one of the frequently used diagnosis tools to detect and classify the breast cancer at the early stage. To improve the diagnosis accuracy, computer-aided diagnosis (CAD) systems are beneficial for detection. Generally, a CAD system consists of four stages: pretreatment, segmentation, features extraction, and classification. In this chapter, the authors present some work in the development of a CAD system in order to segment a breast tumor (microcalcifications) on mammographic images and classify it by choosing the algorithm that gives a good rate using a technique of a vote.