The invention discloses a lesion area classification method and system for a full-view digital pathological section. The invention builds a CSResNet system, carries out learning training of the CSResNet system, achieves automatic segmentation of a lesion area in the full-view digital pathological section, classify a segmented lesion area, and judges the type of the lesion area. The residual attention module in the CSResNet system is combined with attention mechanisms in the channel direction and the space direction at the same time, so that the network can transfer the learning gravity centerto a key area, capable of deciding the category of an input image, in a feature map, and high calculation efficiency, classification precision and recognition capability are achieved.