Breast tumor segmentation in ultrasound images using contextual-information-aware deep adversarial learning framework

作者：

Highlights：

• Efficient automated method for tumor segmentation in breast ultrasound (BUS) images.

• Contextual information-aware conditional generative adversarial learning framework.

• Capture spatial and scale context to handle very different tumor sizes and shapes.

• Two BUS image datasets are used to assess the efficiency of the proposed model.

摘要

•Efficient automated method for tumor segmentation in breast ultrasound (BUS) images.•Contextual information-aware conditional generative adversarial learning framework.•Capture spatial and scale context to handle very different tumor sizes and shapes.•Two BUS image datasets are used to assess the efficiency of the proposed model.

论文关键词：Breast cancer,CAD system,Deep adversarial learning,Ultrasound image segmentation

论文评审过程：Received 29 February 2020, Revised 15 July 2020, Accepted 7 August 2020, Available online 14 August 2020, Version of Record 10 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113870