Extracting information about the rotator cuff from magnetic resonance images using deterministic and random techniques
type: Item
instance of: scholarly article
title: Extracting information about the rotator cuff from magnetic resonance images using deterministic and random techniques
zbMATH Open document ID: 1343.92259
DOI: 10.1155/2015/974562
author: F. A. De Los Ríos
author: M. Paluszny
published in: Computational \& Mathematical Methods in Medicine
publication date: 2016-09-02T00:00:00Z
review text: Summary: We 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.
Mathematics Subject Classification ID: 92C55
zbMATH DE Number: 6622126
zbMATH Keywords: magnetic resonance images
zbMATH Keywords: supraspinatus tendon
zbMATH Keywords: trilinear interpolation
zbMATH Keywords: ellipsoidal triangular patches
Wikidata QID: Q30618166
describes a project that uses: pchip
describes a project that uses: truncdist
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/974562
OpenAlex ID: W2007373278
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DBLP publication ID: journals/cmmm/RiosP15
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description: scientific article; zbMATH DE number 6622126