Abstract: A segmentation method for tumor regions in a pathological image of clear cell renal cell carcinoma based on deep learning includes data acquisition and pre-processing, building and training of a classification network SENet and prediction of tumor regions. The present invention studies clear cell renal cell carcinoma based on pathological images, yielding results with higher reliability than judgments made based on CT or MRI images. The present invention overcomes the drawback that the previous research on clear cell renal cell carcinoma is only limited to judgment on presence by being able to visually provide the position and size of tumor regions, which is convenient for the medical profession to better study the pathogenesis and directions to the treatment of clear cell renal cell carcinoma.