Medical image based breast cancer diagnosis: State of the art and future directions
作者：
Highlights：
• Extensive review over existing automated breast cancer detection techniques is done.
• Machine learning, deep learning and transfer learning based techniques are explored.
• Detail of breast screening imaging modalities and open access datasets is provided.
• Phases of breast tumor detection and classification pipeline are discussed.
• Over 180 research articles related to breast cancer have been summarized.
摘要
•Extensive review over existing automated breast cancer detection techniques is done.•Machine learning, deep learning and transfer learning based techniques are explored.•Detail of breast screening imaging modalities and open access datasets is provided.•Phases of breast tumor detection and classification pipeline are discussed.•Over 180 research articles related to breast cancer have been summarized.
论文关键词：Breast cancer detection and diagnosis,Transfer learning (TL),Deep learning (DL),Machine learning (ML),Computer aided diagnosis (CAD)
论文评审过程：Received 26 June 2020, Revised 2 October 2020, Accepted 3 October 2020, Available online 20 October 2020, Version of Record 10 February 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.114095
