Tumor Detection Based on Normal Model Using Segmentation of Mammary Gland for Breast Ultrasound Images

Abstract

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death in women around the world. Breast cancer screening is essential to breast cancer. Recently, breast ultrasound imaging is one of the most popular techniques. However, the reading of ultrasound images require well-trained radiologists. In order to reduce the burden, Computer-aided detection (CADe) systems are developed to help radiologists in the detection task. However, there are a lot of miss-detection in muscle and fat tissue. To reduce miss-detection, I proposed tumor detection method using mammary segmentation. In the experiments, I show the effectiveness of this method for tumor detection.