March 28, 2024, 4:46 a.m. | Chang Bian, Beth Philips, Tim Cootes, Martin Fergie

cs.CV updates on

arXiv:2403.18501v1 Announce Type: cross
Abstract: Computational analysis of multiplexed immunofluorescence histology data is emerging as an important method for understanding the tumour micro-environment in cancer. This work presents HEMIT, a dataset designed for translating Hematoxylin and Eosin (H&E) sections to multiplex-immunohistochemistry (mIHC) images, featuring DAPI, CD3, and panCK markers. Distinctively, HEMIT's mIHC images are multi-component and cellular-level aligned with H&E, enriching supervised stain translation tasks. To our knowledge, HEMIT is the first publicly available cellular-level aligned dataset that enables H&E …

abstract analysis arxiv cancer computational data dataset eess.iv environment generator image images micro pix2pix translation type understanding work

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