Title:
A PDE Approach for Measuring Tissue Thickness

dc.contributor.author Yezzi, Anthony en_US
dc.contributor.author Prince, Jerry L. en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering en_US
dc.contributor.corporatename Johns Hopkins University. Dept. of Electrical and Computer Engineering en_US
dc.date.accessioned 2013-08-29T20:28:21Z
dc.date.available 2013-08-29T20:28:21Z
dc.date.issued 2003-06
dc.description ©2001 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 distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. en_US
dc.description Presented at the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001. en_US
dc.description DOI: 10.1109/CVPR.2001.990460 en_US
dc.description.abstract We outline an Eulerian framework for computing the thickness of tissues between two simply connected boundaries. Thickness is defined as the length of trajectories which follow a smooth vector field constructed in the region between the boundaries. A pair of partial differential equations (PDEs) are then solved and combined to yield length without requiring the explicit construction of the trajectories. An efficient, stable, and computationally fast solution to these PDEs is found by careful selection of finite differences according to an upwinding condition. The behavior and performance of the method is demonstrated on two simulations and two magnetic resonance imaging data sets in two and three dimensions. These experiments reveal very good performance and show strong potential for application in tissue thickness visualization and quantification. en_US
dc.identifier.citation A. Yezzi and J. Prince, “A PDE Approach for Measuring Tissue Thickness,” Proceedings of Comp. Vision and Pattern Recognition , vol. 1, December 2001, 87-92. en_US
dc.identifier.doi 10.1109/CVPR.2001.990460
dc.identifier.isbn 0-7695-1272-0
dc.identifier.issn 1063-6919
dc.identifier.uri http://hdl.handle.net/1853/48741
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers en_US
dc.subject Eulerian framework en_US
dc.subject PDE approach en_US
dc.subject Anatomical objects en_US
dc.subject Computationally fast solution en_US
dc.subject Explicit construction en_US
dc.subject Finite differences en_US
dc.title A PDE Approach for Measuring Tissue Thickness en_US
dc.type Text
dc.type.genre Article
dspace.entity.type Publication
local.contributor.author Yezzi, Anthony
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
relation.isAuthorOfPublication 53ee63a2-04fd-454f-b094-02a4601962d8
relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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