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Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study.

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Title: Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study.
Authors: Rodner E; Department of Computer Science, Friedrich Schiller University, Jena, Germany.; Corporate Research and Technology, Carl Zeiss AG, Jena, Germany., Bocklitz T; Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, Germany.; Leibniz Institute of Photonic Technology, Jena, Germany., von Eggeling F; Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, Germany.; Leibniz Institute of Photonic Technology, Jena, Germany.; Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany., Ernst G; Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany., Chernavskaia O; Leibniz Institute of Photonic Technology, Jena, Germany., Popp J; Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, Germany.; Leibniz Institute of Photonic Technology, Jena, Germany., Denzler J; Department of Computer Science, Friedrich Schiller University, Jena, Germany., Guntinas-Lichius O; Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.
Source: Head & neck [Head Neck] 2019 Jan; Vol. 41 (1), pp. 116-121. Date of Electronic Publication: 2018 Dec 12.
Publication Type: Journal Article; Observational Study; Research Support, Non-U.S. Gov't
Journal Info: Publisher: John Wiley And Sons Country of Publication: United States NLM ID: 8902541 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0347 (Electronic) Linking ISSN: 10433074 NLM ISO Abbreviation: Head Neck Subsets: MEDLINE
Database: MEDLINE Ultimate
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Description
ISSN:1097-0347
DOI:10.1002/hed.25489