Deep learning segmentation architectures for automatic detection of pancreatic ductal adenocarcinoma in EUS-guided fine-needle biopsy samples based on whole-slide imaging.

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Title: Deep learning segmentation architectures for automatic detection of pancreatic ductal adenocarcinoma in EUS-guided fine-needle biopsy samples based on whole-slide imaging.
Authors: Udriștoiu AL; Faculty of Automation, Computers and Electronics, University of Craiova, Craiova, Romania., Podină N; Department of Gastroenterology, Ponderas Academic Hospital, Bucharest, Romania.; Faculty of Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania., Ungureanu BS; Department of Gastroenterology, University of Medicine and Pharmacy of Craiova, Craiova, Romania.; Research Center of Gastroenterology and Hepatology, University of Medicine and Pharmacy Craiova, Craiova, Romania., Constantin A; Department of Gastroenterology, Ponderas Academic Hospital, Bucharest, Romania., Georgescu CV; Department of Pathology, Clinical Emergency County Hospital of Craiova, Craiova, Romania., Bejinariu N; REGINA MARIA Regional Laboratory, Pathological Anatomy Division, Cluj-Napoca, Romania., Pirici D; Department of Histology, University of Medicine and Pharmacy of Craiova, Craiova, Romania., Burtea DE; Research Center of Gastroenterology and Hepatology, University of Medicine and Pharmacy Craiova, Craiova, Romania., Gruionu L; Faculty of Mechanics, University of Craiova, Craiova, Romania., Udriștoiu S; Faculty of Automation, Computers and Electronics, University of Craiova, Craiova, Romania., Săftoiu A; Department of Gastroenterology, Ponderas Academic Hospital, Bucharest, Romania.; Department of Gastroenterology and Hepatology, Elias University Emergency Hospital, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Source: Endoscopic ultrasound [Endosc Ultrasound] 2024 Nov-Dec; Vol. 13 (6), pp. 335-344. Date of Electronic Publication: 2024 Dec 12.
Publication Type: Journal Article
Journal Info: Publisher: Wolters Kluwer on behalf of Scholar Media Publishing Country of Publication: China NLM ID: 101622292 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2303-9027 (Print) Linking ISSN: 22267190 NLM ISO Abbreviation: Endosc Ultrasound Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2303-9027
DOI:10.1097/eus.0000000000000094