Domain adaptation based self-correction model for COVID-19 infection segmentation in CT images

作者：

Highlights：

• Address the domain shift problem with a limited amount of available datasets.

• An attention and feature domain enhanced model to segment COVID infection.

• A dual-domain enhanced self-correction learning algorithm to refine results.

• Comprehensive evaluation on three cross-site COVID datasets.

摘要

•Address the domain shift problem with a limited amount of available datasets.•An attention and feature domain enhanced model to segment COVID infection.•A dual-domain enhanced self-correction learning algorithm to refine results.•Comprehensive evaluation on three cross-site COVID datasets.

论文关键词：COVID-19 CT segmentation,Domain adaptation,Self-correction learning,Attention mechanism

论文评审过程：Received 30 December 2020, Revised 29 January 2021, Accepted 2 March 2021, Available online 13 March 2021, Version of Record 25 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114848