BRÁZDIL, Tomáš, Matej GALLO, Rudolf NENUTIL, Andrej KUBANDA, Martin TOUFAR a Petr HOLUB. Automated annotations of epithelial cells and stroma in hematoxylin–eosin-stained whole-slide images using cytokeratin re-staining. The Journal of Pathology: Clinical Research. 2022, roč. 8, č. 2, s. 129-142. ISSN 2056-4538. Dostupné z: https://dx.doi.org/10.1002/cjp2.249. |
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@article{1801217, author = {Brázdil, Tomáš and Gallo, Matej and Nenutil, Rudolf and Kubanda, Andrej and Toufar, Martin and Holub, Petr}, article_number = {2}, doi = {http://dx.doi.org/10.1002/cjp2.249}, keywords = {U-Net; artificial intelligence; digital pathology; H&E; immunohistochemistry; deep learning; tissue registration}, language = {eng}, issn = {2056-4538}, journal = {The Journal of Pathology: Clinical Research}, title = {Automated annotations of epithelial cells and stroma in hematoxylin–eosin-stained whole-slide images using cytokeratin re-staining}, url = {https://onlinelibrary.wiley.com/doi/10.1002/cjp2.249}, volume = {8}, year = {2022} }
TY - JOUR ID - 1801217 AU - Brázdil, Tomáš - Gallo, Matej - Nenutil, Rudolf - Kubanda, Andrej - Toufar, Martin - Holub, Petr PY - 2022 TI - Automated annotations of epithelial cells and stroma in hematoxylin–eosin-stained whole-slide images using cytokeratin re-staining JF - The Journal of Pathology: Clinical Research VL - 8 IS - 2 SP - 129-142 EP - 129-142 SN - 20564538 KW - U-Net KW - artificial intelligence KW - digital pathology KW - H&E KW - immunohistochemistry KW - deep learning KW - tissue registration UR - https://onlinelibrary.wiley.com/doi/10.1002/cjp2.249 N2 - The diagnosis of solid tumors of epithelial origin (carcinomas) represents a major part of the workload in clinical histopathology. Distinguishing stroma from epithelium is a critical component of artificial intelligence (AI) methods developed to detect and analyze carcinomas. In this paper, we propose a novel automated workflow that enables large-scale guidance of AI methods to identify the epithelial component. The workflow is based on re-staining existing hematoxylin and eosin (H&E) formalin-fixed paraffin-embedded (FFPE) slides by immunohistochemistry for cytokeratins - cytoskeleton components specific to epithelial cells. We also demonstrate how the automatically generated masks can be used to train modern AI image segmentation based on U-Net, resulting in reliable detection of epithelial regions in previously unseen H&E slides. ER -
BRÁZDIL, Tomáš, Matej GALLO, Rudolf NENUTIL, Andrej KUBANDA, Martin TOUFAR a Petr HOLUB. Automated annotations of epithelial cells and stroma in hematoxylin–eosin-stained whole-slide images using cytokeratin re-staining. \textit{The Journal of Pathology: Clinical Research}. 2022, roč.~8, č.~2, s.~129-142. ISSN~2056-4538. Dostupné z: https://dx.doi.org/10.1002/cjp2.249.
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