摘要
Computational pathology,a field at the intersection of computer science and pathology,leverages digital technology to enhance diagnostic accuracy and efficiency.With the digitization of pathology and the development of artificial intelligence,computational pathology has made significant strides in the automatic analysis of pathology images,including pathological structure segmentation,tumor classification,and prognosis analysis.Driven by large-scale datasets and advanced methods,computational pathology is moving toward building foundation models to reach more general applications.Generative methods provide a new perspective on addressing challenges in computational pathology.However,challenges in data security and model reliability,reproducibility,and clinical application remain.This review outlines the evolution of computational pathology from pathology slide digitization to pathology image analysis,consolidates the development of foundation and generative models in computational pathology,and discusses the key challenges that persist.Finally,we introduce some rising techniques for precision pathology.
基金
supported in part by the Shenzhen Natural Science Fund(the Stable Support Plan Program 20220810144949003)
the Key Technology Development Program of Shenzhen(JSGG20210713091811036)
the Key-Area Research and Development Program of Guangdong Province(2021B0101420005)
the Shenzhen Key Laboratory Foundation(ZDSYS20200811143757022)
the Guangdong Provincial Key Laboratory of Mathematical and Neural Dynamical Systems(2024B1212010004).
