M
Metin N. Gurcan
Researcher at Wake Forest University
Publications - 232
Citations - 8627
Metin N. Gurcan is an academic researcher from Wake Forest University. The author has contributed to research in topics: Image segmentation & Digital pathology. The author has an hindex of 35, co-authored 216 publications receiving 7010 citations. Previous affiliations of Metin N. Gurcan include University of Michigan & iCAD Inc..
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Journal ArticleDOI
Histopathological Image Analysis: A Review
TL;DR: The recent state of the art CAD technology for digitized histopathology is reviewed and the development and application of novel image analysis technology for a few specific histopathological related problems being pursued in the United States and Europe are described.
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Digital pathology and artificial intelligence
TL;DR: Advances in digital slide-based image diagnosis for cancer along with some challenges and opportunities for artificial intelligence in digital pathology are discussed.
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Pten in stromal fibroblasts suppresses mammary epithelial tumours
Anthony J. Trimboli,Carmen Z. Cantemir-Stone,Fu Li,Julie A. Wallace,Anand S. Merchant,Nicholas Creasap,John C. Thompson,Enrico Caserta,Hui Wang,Jean-Leon Chong,Shan Naidu,Guo Wei,Sudarshana M. Sharma,Julie A. Stephens,Soledad Fernandez,Metin N. Gurcan,Michael Weinstein,Sanford H. Barsky,Lisa D. Yee,Thomas J. Rosol,Paul C. Stromberg,Michael L. Robinson,Francois Pepin,Michael Hallett,Morag Park,Michael C. Ostrowski,Gustavo Leone,Gustavo Leone +27 more
TL;DR: The Pten–Ets2 axis is identified as a critical stroma-specific signalling pathway that suppresses mammary epithelial tumours and ameliorated disruption of the tumour microenvironment.
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Lung nodule detection on thoracic computed tomography images: Preliminary evaluation of a computer-aided diagnosis system
Metin N. Gurcan,Berkman Sahiner,Nicholas Petrick,Heang Ping Chan,Ella A. Kazerooni,Philip N. Cascade,Lubomir M. Hadjiiski +6 more
TL;DR: Compared to FP reduction with LDA alone, the inclusion of rule-based classification lead to an improvement in detection accuracy for the CAD system, and the free response receiver operating characteristic (FROC) curve improved over the entire sensitivity and specificity ranges of interest.
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Mitosis detection in breast cancer histological images An ICPR 2012 contest
Ludovic Roux,Daniel Racoceanu,Nicolas Loménie,Maria S. Kulikova,Humayun Irshad,Jacques Klossa,Frédérique Capron,Catherine Genestie,Gilles Le Naour,Metin N. Gurcan +9 more
TL;DR: A main objective of this contest was to propose a database of mitotic cells on digitized breast cancer histopathology slides to initiate works on automated mitotic cell detection, but the database provided is by far too small for a good assessment of reliability and robustness of the proposed algorithms.