Multi-feature deep information bottleneck network for breast cancer classification in contrast enhanced spectral mammography

作者：

Highlights：

• First information bottleneck based-deep learning study for classifying breast cancer.

• Multi-feature deep information bottleneck is introduced.

• The features between contrast enhanced spectral mammography are fully explored.

• Multiple image features are considered simultaneously in relation to the labels.

摘要

•First information bottleneck based-deep learning study for classifying breast cancer.•Multi-feature deep information bottleneck is introduced.•The features between contrast enhanced spectral mammography are fully explored.•Multiple image features are considered simultaneously in relation to the labels.

论文关键词：Contrast enhanced spectral mammography,Classification,Deep learning,Multi-feature,Information bottleneck

论文评审过程：Received 25 February 2022, Revised 25 May 2022, Accepted 16 June 2022, Available online 17 June 2022, Version of Record 22 June 2022.

论文官网地址：https://doi.org/10.1016/j.patcog.2022.108858