Abstract: Emergence of whole-slide imaging initiates the digital pathology. With the improvement of storage technology and the rapid development of internet and computer technologies, deep learning methods are widely used in the analysis of pathological images. The goal is to solve the problem of redundant and complicated information of pathological images that causes difficulty in diagnosis and analysis, alleviate the tedious analysis work of pathologists, and improve the accuracy of results. This paper reviewed the commonly used deep learning methods for pathological analysis and the application of deep learning in various fields of pathological analysis, and briefly discussed some challenges and opportunities of deep learning in pathological analysis.

Key words: Deep learning, Artificial intelligence, Digital pathology, Whole-slide imaging