J Korean Soc Radiol.  2020 Nov;81(6):1274-1289. 10.3348/jksr.2020.0171.

Development of an Optimized Deep Learning Model for Medical Imaging

Affiliations
  • 1Department of Biomedical Engineering, Gachon University, Incheon, Korea.

Abstract

Deep learning has recently become one of the most actively researched technologies in the field of medical imaging. The availability of sufficient data and the latest advances in algorithms are important factors that influence the development of deep learning models. However, several other factors should be considered in developing an optimal generalized deep learning model. All the steps, including data collection, labeling, and pre-processing and model training, validation, and complexity can affect the performance of deep learning models. Therefore, appropriate optimization methods should be considered for each step during the development of a deep learning model. In this review, we discuss the important factors to be considered for the optimal development of deep learning models.

Keyword

Deep Learning; Algorithms; Data Collection; Product Labeling; Diagnostic Imaging
Full Text Links
  • JKSR
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2022 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr