J Korean Soc Radiol.  2019 Mar;80(2):202-212. 10.3348/jksr.2019.80.2.202.

The Latest Trends in the Use of Deep Learning in Radiology Illustrated Through the Stages of Deep Learning Algorithm Development

Affiliations
  • 1Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. sdo@mgh.harvard.edu
  • 2Department of Radiology, Samsung Medical Center, Seoul, Korea.

Abstract

Recently, considerable progress has been made in interpreting perceptual information through artificial intelligence, allowing better interpretation of highly complex data by machines. Furthermore, the applications of artificial intelligence, represented by deep learning technology, to the fields of medical and biomedical research are increasing exponentially. In this article, we will explain the stages of deep learning algorithm development in the field of medical imaging, namely topic selection, data collection, data exploration and refinement, algorithm development, algorithm evaluation, and clinical application; we will also discuss the latest trends for each stage.

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