Emerging Research Directions of Deep Learning for Pathology Image Analysis

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.