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Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors

In this paper, we consider nonlinear partial differential equations (PDEs) of diffusion/advection type underlying most problems in image analysis. As case study, we address the segmentation of medical structures. We perform a comparative study of numerical algorithms arising from using the semi-impl...

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Detalles Bibliográficos
Autores principales: D'Amore, Luisa, Casaburi, Daniela, Marcellino, Livia, Murli, Almerico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3191783/
https://www.ncbi.nlm.nih.gov/pubmed/22007187
http://dx.doi.org/10.1155/2011/680765
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author D'Amore, Luisa
Casaburi, Daniela
Marcellino, Livia
Murli, Almerico
author_facet D'Amore, Luisa
Casaburi, Daniela
Marcellino, Livia
Murli, Almerico
author_sort D'Amore, Luisa
collection PubMed
description In this paper, we consider nonlinear partial differential equations (PDEs) of diffusion/advection type underlying most problems in image analysis. As case study, we address the segmentation of medical structures. We perform a comparative study of numerical algorithms arising from using the semi-implicit and the fully implicit discretization schemes. Comparison criteria take into account both the accuracy and the efficiency of the algorithms. As measure of accuracy, we consider the Hausdorff distance and the residuals of numerical solvers, while as measure of efficiency we consider convergence history, execution time, speedup, and parallel efficiency. This analysis is carried out in a multicore-based parallel computing environment.
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spelling pubmed-31917832011-10-17 Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors D'Amore, Luisa Casaburi, Daniela Marcellino, Livia Murli, Almerico Int J Biomed Imaging Research Article In this paper, we consider nonlinear partial differential equations (PDEs) of diffusion/advection type underlying most problems in image analysis. As case study, we address the segmentation of medical structures. We perform a comparative study of numerical algorithms arising from using the semi-implicit and the fully implicit discretization schemes. Comparison criteria take into account both the accuracy and the efficiency of the algorithms. As measure of accuracy, we consider the Hausdorff distance and the residuals of numerical solvers, while as measure of efficiency we consider convergence history, execution time, speedup, and parallel efficiency. This analysis is carried out in a multicore-based parallel computing environment. Hindawi Publishing Corporation 2011 2011-10-10 /pmc/articles/PMC3191783/ /pubmed/22007187 http://dx.doi.org/10.1155/2011/680765 Text en Copyright © 2011 Luisa D'Amore et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
D'Amore, Luisa
Casaburi, Daniela
Marcellino, Livia
Murli, Almerico
Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors
title Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors
title_full Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors
title_fullStr Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors
title_full_unstemmed Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors
title_short Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors
title_sort numerical solution of diffusion models in biomedical imaging on multicore processors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3191783/
https://www.ncbi.nlm.nih.gov/pubmed/22007187
http://dx.doi.org/10.1155/2011/680765
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