Handling imbalanced medical image data: A deep-learning-based one-class classification approach

作者：

Highlights：

• A novel deep-learning-based model for the data imbalance problem.

• Effective perturbing operations to capture single-class-relevant features.

• State-of-the-art performance on four imbalanced medical image datasets.

摘要

•A novel deep-learning-based model for the data imbalance problem.•Effective perturbing operations to capture single-class-relevant features.•State-of-the-art performance on four imbalanced medical image datasets.

论文关键词：Medical image classification,Data imbalance,Deep learning,Image complexity

论文评审过程：Received 2 March 2020, Revised 20 June 2020, Accepted 17 July 2020, Available online 7 August 2020, Version of Record 23 August 2020.

论文官网地址：https://doi.org/10.1016/j.artmed.2020.101935