Segmentation of MR Images by Using Grow and Learn Network on FPGAs

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dc.contributor.authorCinar, Salim
dc.contributor.authorKurnaz, Mehmet Nadir
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2013
dc.departmentNiğde ÖHÜ
dc.description35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) -- JUL 03-07, 2013 -- Osaka, JAPAN
dc.description.abstractImage segmentation is one of the mostly used procedures in the medical image processing applications. Due to the high resolution characteristics of the medical images and a large amount of computational load in mathematical methods, medical image segmentation process has an excessive computational complexity. Recently, FPGA implementation has been applied in many areas due to its parallel processing capability. In this study, neighbor-pixel-intensity based method for feature extraction and Grow and Learn (GAL) network for segmentation process are proposed. The proposed method is comparatively examined on both PC and FPGA platforms.
dc.description.sponsorshipIEEE Engn Med Biol Soc, Japanese Soc Med & Biol Engn
dc.identifier.endpage4073
dc.identifier.isbn978-1-4577-0216-7
dc.identifier.issn1557-170X
dc.identifier.pmid24110626
dc.identifier.startpage4070
dc.identifier.urihttps://hdl.handle.net/11480/4438
dc.identifier.wosWOS:000341702104129
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakPubMed
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
dc.relation.ispartofseriesIEEE Engineering in Medicine and Biology Society Conference Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleSegmentation of MR Images by Using Grow and Learn Network on FPGAs
dc.typeConference Object

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