Kim Young Jae, Kim Kwang Gi
Taehan Yongsang Uihakhoe Chi. 2020 Nov;81(6):1274-1289. doi: 10.3348/jksr.2020.0171. Epub 2020 Nov 30.
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.
深度学习最近已成为医学成像领域中研究最为活跃的技术之一。充足数据的可用性以及算法的最新进展是影响深度学习模型发展的重要因素。然而，在开发最优的通用深度学习模型时，还应考虑其他几个因素。所有步骤，包括数据收集、标注、预处理以及模型训练、验证和复杂度，都会影响深度学习模型的性能。因此，在深度学习模型开发过程中的每个步骤都应考虑适当的优化方法。在本综述中，我们讨论了深度学习模型最优开发中应考虑的重要因素。
