Artificial intelligence in tumor subregion analysis based on medical imaging: A review. Issue 7 (24th June 2021)

• Record Type: Journal Article
• Authors: Lin, Mingquan; Wynne, Jacob F.; Zhou, Boran; Wang, Tonghe; Lei, Yang; Curran, Walter J.; Liu, Tian; Yang, Xiaofeng
• Is Part Of: Journal of applied clinical medical physics. Volume 22:Issue 7(2021)
• Page Start: 10
• Page End: 26
• Publication Date: 2021-06-24
• Subjects: tumor subregion analysis -- artificial intelligence -- deep learning -- medical imaging -- medical image analysis; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13321
• Languages: English
• ISSNs: 1526-9914

Abstract

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.