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dc.contributor.authorPham, Duc Duyen_US
dc.contributor.authorMorariu, Cosmin Adrianen_US
dc.contributor.authorTerheiden, Tobiasen_US
dc.contributor.authorLandgraeber, Stefanen_US
dc.contributor.authorJäger, Marcusen_US
dc.contributor.authorPauli, Josefen_US
dc.contributor.editorStefan Bruckner and Anja Hennemuth and Bernhard Kainz and Ingrid Hotz and Dorit Merhof and Christian Riederen_US
dc.date.accessioned2017-09-06T07:12:41Z
dc.date.available2017-09-06T07:12:41Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-036-9
dc.identifier.issn2070-5786
dc.identifier.urihttp://dx.doi.org/10.2312/vcbm.20171243
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20171243
dc.description.abstractIn this paper, we propose a novel hybrid level set approach that locally balances the combined use of both Gradient Vector Flow and region based energy cost function by means of the Bhattacharyya coefficient. The local neighborhood of each contour point is naturally divided into an area encapsulated and one excluded by the contour. We propose utilizing the Bhattacharyya coefficient of the intensity distributions of these local areas to determine a point-wise weighting scheme for the curve propagation. The performance of our method regarding segmentation quality is evaluated on the segmentation of the hip joint in 10 MRI data sets. Our proposed method shows a clear improvement compared to conventional 3D level set approaches.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCCS Concepts
dc.subjectComputing methodologies
dc.subjectImage segmentation
dc.subjectImage processing
dc.subjectApplied computing
dc.subjectImaging
dc.titleMRI Hip Joint Segmentation: A Locally Bhattacharyya Weighted Hybrid 3D Level Set Approachen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.description.sectionheadersShort Papers
dc.identifier.doi10.2312/vcbm.20171243
dc.identifier.pages113-117


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