A SYNOPSIS OF MACHINE AND DEEP LEARNING IN MEDICAL PHYSICS AND RADIOLOGY

Emam Z. A. A., ADA E.

JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES, vol.6, no.3, pp.946-957, 2022 (ESCI, TRDizin) identifier identifier

  • Publication Type: Article / Review
  • Volume: 6 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.30621/jbachs.960154
  • Journal Name: JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES
  • Journal Indexes: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Page Numbers: pp.946-957
  • Keywords: deep learning, machine learning, radiology, radiation oncology, medical physics
  • Dokuz Eylül University Affiliated: Yes

Abstract

Machine learning (ML) and deep learning (DL) techniques introduced within the fields of medical physics, radiology, and radiation oncology (RO) have come a long way in the past few years. A great many applications have proven to be an efficacious automated diagnosis and radiotherapy system. This paper outlines DL's general concepts and principles, key computational methods, and resources, as well as the implementation of automated models in radiology and RO research. In addition, the potential challenges and solutions of DL technology are also discussed.