dc.creatorde Los Ríos, F. A.
dc.creatorPaluszny, M.
dc.date.accessioned2020-08-19T14:43:29Z
dc.date.accessioned2022-09-22T13:44:56Z
dc.date.available2020-08-19T14:43:29Z
dc.date.available2022-09-22T13:44:56Z
dc.date.created2020-08-19T14:43:29Z
dc.identifierISSN: 1748-670X
dc.identifierEISSN: 1748-6718
dc.identifierhttps://repository.urosario.edu.co/handle/10336/27715
dc.identifierhttps://doi.org/10.1155/2015/974562
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3432039
dc.description.abstractWe consider some methods to extract information about the rotator cuff based on magnetic resonance images; the study aims to define an alternative method of display that might facilitate the detection of partial tears in the supraspinatus tendon. Specifically, we are going to use families of ellipsoidal triangular patches to cover the humerus head near the affected area. These patches are going to be textured and displayed with the information of the magnetic resonance images using the trilinear interpolation technique. For the generation of points to texture each patch, we propose a new method that guarantees the uniform distribution of its points using a random statistical method. Its computational cost, defined as the average computing time to generate a fixed number of points, is significantly lower as compared with deterministic and other standard statistical techniques.
dc.languageeng
dc.publisherHindawi Publishing Corporation
dc.relationComputational and Mathematical Methods in Medicine, ISSN: 1748-670X;EISSN: 1748-6718, Vol.2015 (2015); 6 pp.
dc.relationhttp://downloads.hindawi.com/journals/cmmm/2015/974562.pdf
dc.relationComputational and Mathematical Methods in Medicine
dc.relationVol. 2015
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAbierto (Texto Completo)
dc.sourceComputational and Mathematical Methods in Medicine
dc.sourceinstname:Universidad del Rosario
dc.sourcereponame:Repositorio Institucional EdocUR
dc.titleExtracting information about the rotator cuff from magnetic resonance images using deterministic and random techniques
dc.typearticle


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