CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H&E-stained histological images

Volume: 132, Pages: 104349 - 104349
Published: May 1, 2021
Abstract
Nuclei instance segmentation plays an important role in the analysis of hematoxylin and eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent the state-of-the-art in automatic nuclei instance segmentation, annotated datasets are required to train these models. There are two main types of tissue processing protocols resulting in formalin-fixed paraffin-embedded samples (FFPE) and frozen tissue samples (FS),...
Paper Details
Title
CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H&E-stained histological images
Published Date
May 1, 2021
Volume
132
Pages
104349 - 104349
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