Abstract
Medical imaging is widely used in the diagnosis and treatment of cancer, and artificial intelligence (AI) has achieved tremendous success in medical image analysis. This paper reviews AI-based tumor subregion analysis in medical imaging. We summarize the latest AI-based methods for tumor subregion analysis and their applications. Specifically, we categorize the AI-based methods by training strategy: supervised and unsupervised. A detailed review of each category is presented, highlighting important contributions and achievements. Specific challenges and potential applications of AI in tumor subregion analysis are discussed.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 10-26 |
| Number of pages | 17 |
| Journal | Journal of Applied Clinical Medical Physics |
| Volume | 22 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2021 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- artificial intelligence
- deep learning
- medical image analysis
- medical imaging
- tumor subregion analysis
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