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Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning
2020
International Conference on Medical Imaging with Deep Learning
An emerging technology in cancer care and research is the use of histopathology whole slide images (WSI). Leveraging computation methods to aid in WSI assessment poses unique challenges. WSIs, being extremely high resolution giga-pixel images, cannot be directly processed by convolutional neural networks (CNN) due to huge computational cost. For this reason, state-of-the-art methods for WSI analysis adopt a two-stage approach where the training of a tile encoder is decoupled from the tile
dblp:conf/midl/XieMVCYCF20
fatcat:cpawx67uyre5fowibxlwtrtnpi