000000385 001__ 385
000000385 005__ 20250424232520.0
000000385 0247_ $$2DOI$$a10.6083/M43X84MT
000000385 037__ $$aETD
000000385 245__ $$aClassification and retrieval of endoscopic images from the clinical outcomes research initiative (CORI) collection
000000385 260__ $$bOregon Health and Science University
000000385 269__ $$a2009
000000385 336__ $$aThesis
000000385 502__ $$bM.S.
000000385 520__ $$aTraditionally, image retrieval systems have been text-based, relying on the annotations or captions associated with the images. Although text-based information retrieval methods are mature and well-researched, they are limited by the quality and availability of the annotations associated with the images. Advances in techniques in computer vision have led to methods for using the  image as the search entity.  Our project aimed to create an image retrieval system with a set of 1500 upper endoscopic images from the Clinical Outcomes Research Initiative Collection.
000000385 540__ $$fCC BY
000000385 542__ $$fIn copyright - single owner
000000385 650__ $$aLibraries$$021476
000000385 650__ $$aDatabase Management Systems$$017388
000000385 650__ $$aInformation Systems$$020807
000000385 650__ $$aInformation Storage and Retrieval$$028998
000000385 650__ $$aPattern Recognition, Automated$$023678
000000385 691__ $$aSchool of Medicine$$041369
000000385 692__ $$aDepartment of Medical Informatics and Clinical Epidemiology$$041422
000000385 7001_ $$aKalpathy-Cramer, Jayashree$$uOregon Health and Science University$$041354
000000385 7201_ $$aHersh, William$$uOregon Health and Science University$$041354$$7Personal$$eAdvisor
000000385 8564_ $$9a9542e46-311d-4552-83e3-a9f27503e669$$s1140865$$uhttps://digitalcollections.ohsu.edu/record/385/files/386_etd.pdf$$ePublic$$2b6680f858cbcec49b224683e513b584e$$31
000000385 905__ $$a/rest/prod/g7/32/d8/99/g732d899x
000000385 909CO $$ooai:digitalcollections.ohsu.edu:385$$pstudent-work
000000385 980__ $$aBiomedical Informatics