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.