SAP-cGAN: Adversarial learning for breast mass segmentation in digital mammogram based on superpixel average pooling.
Journal:
Medical physics
Published Date:
Jan 10, 2021
Abstract
PURPOSE: Breast mass segmentation is a prerequisite step in the use of computer-aided tools designed for breast cancer diagnosis and treatment planning. However, mass segmentation remains challenging due to the low contrast, irregular shapes, and fuzzy boundaries of masses. In this work, we propose a mammography mass segmentation model for improving segmentation performance.