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On the acceptance of "fake" histopathology: A study on froz..:

Mario Siller ; Lea Maria Stangassinger ; Christina Kreutzer...
http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2022;volume=13;issue=1;spage=6;epage=6;aulast=Siller. , 2022

Link: https://doi.org/10.4103/jpi.jpi_53_21

RT Journal
T1 <Title>On the acceptance of "fake" histopathology: A study on frozen sections optimized with deep learning</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:f39383205bbc400aa463d53c993dd651&Exemplar=1&LAN=DE
				
A1 Mario Siller
A1 Lea Maria Stangassinger
A1 Christina Kreutzer
A1 Peter Boor
A1 Roman D Bulow
A1 Theo J F Kraus
A1 Saskia von Stillfried
A1 Soraya Wolfl
A1 Sebastien Couillard-Despres
A1 Gertie Janneke Oostingh
A1 Anton Hittmair
A1 Michael Gadermayr
PB Elsevier
YR 2022
K1 frozen sections
K1 generative adversarial networks
K1 histology
K1 paraffin sections
K1 thyroid cancer
K1 whole slide imaging
K1 Computer applications to medicine. Medical informatics
K1 R858-859.7
K1 Pathology
K1 RB1-214
JF http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2022;volume=13;issue=1;spage=6;epage=6;aulast=Siller
LK http://dx.doi.org/https://doi.org/10.4103/jpi.jpi_53_21
DO https://doi.org/10.4103/jpi.jpi_53_21
SF ELIB - SuUB Bremen

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