期刊
MEDICAL IMAGE ANALYSIS
卷 79, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.media.2022.102470
关键词
Explainable artificial intelligence; Interpretable deep learning; Medical image analysis; Deep learning; Survey
类别
资金
- Dutch Cancer Society [10755]
This survey examines the applications of explainable artificial intelligence (XAI) in deep learning-based medical image analysis. It introduces a framework for classifying deep learning-based medical image analysis methods based on XAI criteria. The survey also categorizes and investigates XAI techniques in medical image analysis according to the framework and anatomical location. The paper concludes by discussing future opportunities for XAI in medical image analysis.
With an increase in deep learning-based methods, the call for explainability of such methods grows, es-pecially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of explainable artificial intelligence (XAI) used in deep learning-based medical image analysis. A framework of XAI criteria is introduced to classify deep learning-based medical image analysis meth-ods. Papers on XAI techniques in medical image analysis are then surveyed and categorized according to the framework and according to anatomical location. The paper concludes with an outlook of future opportunities for XAI in medical image analysis. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
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