A fully automatic framework for evaluating cosmetic results of breast conserving therapy

著者: Chenqi Guo, Tamara L. Smith, Qianli Feng, Fabian Benitez-Quiroz, Frank A. Vicini, Douglas W. Arthur, Julia White, Aleix M. Martı́nez - Machine Learning with Applications 2022 被引用: 10

Machine Learning Breast Cosmetic evaluation algorithm leveraging the state-of-the-art Deep Learning algorithms for breast detection and contour annotation, 2. a novel set of Breast Cosmesis features, 3. a new Breast Cosmetic dataset consisting 3k+ images from three clinical trials with human annotations on both breast components and their cosmesis scores. We show our fully-automatic framework can achieve comparable performance to state-of-the-art without the need of human inputs, leading to a more objective, low-cost and scalable solution for breast cosmetic evaluation in breast cancer treatment.