The Latest Trends in the Use of Deep Learning in Radiology Illustrated Through the Stages of Deep Learning Algorithm Development
10.3348/jksr.2019.80.2.202
- Author:
Kyoung Doo SONG
1
;
Myeongchan KIM
;
Synho DO
Author Information
1. Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. sdo@mgh.harvard.edu
- Publication Type:Review
- From:Journal of the Korean Radiological Society
2019;80(2):202-212
- CountryRepublic of Korea
- Language:Korean
-
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.
