@inproceedings{9c705dc342614df5b0eba2e77ca86584,
title = "Emerging Research Directions of Deep Learning for Pathology Image Analysis",
abstract = "Digital pathology image analysis has become a new emerging research trend in the medical domain. AI methods have been shown their effectiveness on conventional vision applications. However, applying AI methods on pathology image analysis is far from easy. Many practical challenging issues arise including pathology image analysis under insufficient and inaccurate annotations, recognizing pathology images of different data distributions, and training AI models based on decentralized data sources. In this paper, we focus on discussing these challenging issues of AI approaches for pathology image analysis. A survey of relevant pathology applications will be also conducted. The research directions of these techniques for future development in pathology image analysis are also presented in this paper.",
keywords = "artificial intelligence, computer vision, deep learning, pathology",
author = "Chung, {Pau Choo} and Yang, {Wei Jong} and Wu, {Tsung Hsuan} and Huang, {Chun Rong} and Hsu, {Yi Yu}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022 ; Conference date: 13-10-2022 Through 15-10-2022",
year = "2022",
doi = "10.1109/BioCAS54905.2022.9948651",
language = "English",
series = "BioCAS 2022 - IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Systems for a Better Future, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "100--104",
booktitle = "BioCAS 2022 - IEEE Biomedical Circuits and Systems Conference",
address = "美國",
}