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Colonic Polyp Classification using Projection Image and Convolutional Neural Network

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dc.contributor.authorTulum, Gokalp
dc.contributor.authorOsman, Onur
dc.contributor.authorBolat, Bulent
dc.contributor.authorDandin, Ozgur
dc.contributor.authorErgin, Tuncer
dc.contributor.authorCuce, Ferhat
dc.date.accessioned2026-06-27T14:18:56Z
dc.date.issued2019
dc.description.abstractNow adays, Computer-aided detection (CAD) systems are used to assist radiologists to detect colonic polyps. In this work, we aimed to develop convolutional neural network based classification system for automated detection of polyps. 2D projection images of polyps were used as the input of convolutional neural network. Our classification system performs at 91.89% sensitivity for polyps with 0 false positives per dataset.en
dc.identifier.isbn978-1-7281-1013-4
dc.identifier.urihttps://hdl.handle.net/20.500.14981/59162
dc.identifier.wos000491430200018
dc.language.isotur
dc.publisherIEEE
dc.relation.conferenceInternational Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science (EBBT)
dc.relation.ispartof2019 SCIENTIFIC MEETING ON ELECTRICAL-ELECTRONICS & BIOMEDICAL ENGINEERING AND COMPUTER SCIENCE (EBBT)
dc.subjectPolyp classification
dc.subjectconvolutional neural network
dc.subjectCAD
dc.subjectComputer Science
dc.subjectEngineering
dc.titleColonic Polyp Classification using Projection Image and Convolutional Neural Network
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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