Registration Of Breast Surface Data Before And After Surgical Intervention

Surgery planing of breast cancer interventions is gaining importance among physicians, who recognize value in discussing the possible aesthetic outcomes of surgery with patients. Research is been propelled to create patient-specific breast models, but breast image registration algorithms are still limited, particularly for the purpose of matching pre- and post-surgical data of patient's breast surfaces. Yet, this is a fundamental task to learn prediction models of breast healing process after surgery. In this paper, a coarse-to-fine registration strategy is proposed to match breast surface data acquired before and after surgery. Methods are evaluated in their ability to register surfaces in an anatomical reliable way, and results suggest proper alignment adequated to be used as input to train deformable models.