TY - JOUR
T1 - The latest trends in the use of deep learning in radiology illustrated through the stages of deep learning algorithm development
AU - Song, Kyoung Doo
AU - Kim, Myeongchan
AU - Do, Synho
N1 - Publisher Copyright:
© 2019 The Korean Society of Radiology.
PY - 2019/3
Y1 - 2019/3
N2 - Recently, considerable progress has been made in interpreting perceptual information throughartificial 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, wewill 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 foreach stage.
AB - Recently, considerable progress has been made in interpreting perceptual information throughartificial 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, wewill 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 foreach stage.
KW - Algorithms
KW - Artificial Intelligence
KW - Deep Learning
UR - https://www.scopus.com/pages/publications/85077216243
U2 - 10.3348/jksr.2019.80.2.202
DO - 10.3348/jksr.2019.80.2.202
M3 - Review article
AN - SCOPUS:85077216243
SN - 1738-2637
VL - 80
SP - 202
EP - 212
JO - Journal of the Korean Society of Radiology
JF - Journal of the Korean Society of Radiology
IS - 2
ER -