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Integrating region and edge information for the automatic segmentation of interventional magnetic resonance images of the shoulder complex

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dc.contributor.author Tremblay, ME
dc.contributor.author Branzan Albu, A
dc.contributor.author Hebert, L
dc.contributor.author Laurendeau, D
dc.date.accessioned 2009-07-21T20:40:32Z
dc.date.available 2009-07-21T20:40:32Z
dc.date.copyright 2004 en
dc.date.issued 2004
dc.identifier.citation Tremblay, ME, Branzan Albu, A, Hebert L, Laurendeau, D, Integrating region and edge information for the automatic segmentation of interventional magnetic resonance images of the shoulder complex, Proceedings of the First Canadian Conference on Computer and Robot Vision (CRV'04) en
dc.identifier.uri http://hdl.handle.net/1828/1469
dc.description ©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. en
dc.description.abstract This paper proposes a new 2D segmentation method for MR shoulder images. Due to the significant length of the image sequences, we aim at minimizing the user intervention in the segmentation process. Our method integrates region and edge information in a coherent manner. In fact, the edge information is used in the definition of an adaptive similarity measure for iterative pixel aggregation. The seeds for the region growing process are defined automatically, which is essential for processing long image sequences with variable average brightness. Moreover, the proposed segmentation approach implements parallel region growing processes, and allows for dynamic region merging at successive iterations. To assess the performance of the proposed approach, we followed a standard methodology used for validating 2D segmentation, as well as a quantitative and qualitative evaluation of the 3D shoulder model reconstructed from the segmented image sequences. en
dc.language.iso en en
dc.publisher IEEE en
dc.title Integrating region and edge information for the automatic segmentation of interventional magnetic resonance images of the shoulder complex en
dc.type Article en


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