AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review.

Journal: Nuclear medicine communications
PMID:

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.

Authors

  • Nikolaos I Papandrianos
    Department of Energy Systems, University of Thessaly, Gaiopolis Campus, 41500, Larisa, Greece. npapandrianos@uth.gr.
  • Ioannis D Apostolopoulos
    Department of Medical Physics, School of Medicine, University of Patras, 26504, Patras, Greece. ece7216@upnet.gr.
  • Anna Feleki
    Department of Energy Systems, University of Thessaly, Gaiopolis Campus, 41500, Larisa, Greece.
  • Serafeim Moustakidis
    AIDEAS OÜ, Narva mnt 5, Tallinn, Harju maakond, 10117, Estonia.
  • Konstantinos Kokkinos
    Department of Energy Systems, University of Thessaly, Larisa, Greece.
  • Elpiniki I Papageorgiou
    Department of Informatics & Computer Technology, Technological Educational Institute of Lamia, Greece.