AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review. Issue 1 (15th November 2022)

• Record Type: Journal Article
• Authors: Papandrianos, Nikolaos I.; Apostolopoulos, Ioannis D.; Feleki, Anna; Moustakidis, Serafeim; Kokkinos, Konstantinos; Papageorgiou, Elpiniki I.
• Is Part Of: Nuclear medicine communications. Volume 44:Issue 1(2023)
• Page Start: 1
• Page End: 11
• Publication Date: 2022-11-15
• Subjects: deep learning -- classification -- cardiovascular diseases -- nuclear medicine -- SPECT -- artificial intelligence; Nuclear medicine -- Periodicals; 616.07575
• DOI: 10.1097/MNM.0000000000001634
• Languages: English
• ISSNs: 0143-3636

Abstract

Abstract : In the last few years, deep learning has made a breakthrough and established its position in machine learning classification problems in medical image analysis. Deep learning has recently displayed remarkable applicability in a range of different medical applications, as well as in nuclear cardiology. This paper implements a literature review protocol and reports the latest advances in artificial intelligence (AI)-based classification in SPECT myocardial perfusion imaging in heart disease diagnosis. The representative and most recent works are reported to demonstrate the use of AI and deep learning technologies in medical image analysis in nuclear cardiology for cardiovascular diagnosis. This review also analyses the primary outcomes of the presented research studies and suggests future directions focusing on the explainability of the deployed deep-learning systems in clinical practice.