Intelligent analysis of whole slide imaging
WANG Jingchuan
HU Xifeng
XU Hongji
LIU Zhi
Abstract：With the rapid advancement of digital histopathology,whole slide imaging(WSI)has seen widespread application in the medical field.In recent years,the rapid development of deep learning algorithms has provided new opportunities for WSI research.To better analyze WSI and fully utilize its rich detailed information,and extract features from WSI images by using deep learning algo-rithms,thereby accomplishing various downstream tasks has become a research hotpot.We provide a comprehensive review of the intel-ligent analysis of WSI images.Firstly,several methods for color normalization using deep learning are introduct.Subsequently,we re-view different strategies employed in various studies for input data selection.Finally,we summarize the applications of deep learning in the three major downstream tasks of WSI images:segmentation,classification,and prediction,and discuss the challenges and future directions for the application of deep learning in WSI.
Keywords：Deep learningWhole slide imagingDigital pathology image analysisConvolutional neural networksHistopathological image
Publication Date：2024-06-28
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：7( 175-180,222 )