dc.creatorRamírez J,Esmitt
dc.creatorTemoche,Pablo
dc.creatorCarmona,Rhadamés
dc.date2013-08-01
dc.date.accessioned2023-09-25T18:35:16Z
dc.date.available2023-09-25T18:35:16Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002013000200004
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838457
dc.descriptionAbstract The representation of an image as a flow network has gained an increased interest in research for the 2D and 3D segmentation field. One of these segmentation approaches consists in applying a minimum cut algorithm to separate the image in background and foreground. The most remarkable algorithm to segment a 2D image using this approach is GrabCut. This article presents a novel segmentation of 3D image using GrabCut implemented on the GPU. We proposed a scheme where a volume dataset is used as input, instead of a 2D image. The original GrabCut algorithm is adapted to be executed on the GPU efficiently. Our algorithm is fully parallel and is optimized to run on Nvidia CUDA. Tests performed showed excellent results with different volumes, reducing the computation time and maintaining a correct separation background/foreground.
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.16 n.2 2013
dc.subjectvolume segmentation
dc.subjectGrabCut
dc.subjectflow network
dc.subjectminimum cut
dc.subjectPush-Relabel
dc.titleA volume segmentation approach based on GrabCut
dc.typeinfo:eu-repo/semantics/article


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