A Review of Artificial Intelligence in Tumor Pathology Image Analysis

Abstract

Accurate diagnosis of tumors is crucial to the treatment and prognosis of patients. Pathological diagnosis is regarded as the "gold standard" of tumor diagnosis, which helps to detect the disease at an early stage and formulate precise treatment plans for patients. However, traditional pathology diagnosis relies heavily on the expertise and diagnostic experience of physicians, making the quality and accuracy of pathology diagnosis largely dependent on their individual capabilities. With the popularization of Whole Slide Image (WSI) technology, the application of AI in pathology has gained significant momentum. With its powerful analyzing ability, AI has been widely used in computational pathology, especially in pathology-assisted diagnosis, showing great potential. This paper first explores two core tasks of AI in the field of pathology image analysis - image segmentation and image classification. Finally, it looks at the challenges and opportunities facing the field.