Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors | Zendy

Luisa D’Amore | Zendy; Daniela Casaburi | Zendy; Livia Marcellino | Zendy; A. Murli | Zendy

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Numerical Solution of Diffusion Models in Biomedical Imaging on Multicore Processors

Author(s) -

Luisa D’Amore,

Daniela Casaburi,

Livia Marcellino,

A. Murli

Publication year - 2011

Publication title -

international journal of biomedical imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.626

H-Index - 41

eISSN - 1687-4196

pISSN - 1687-4188

DOI - 10.1155/2011/680765

Subject(s) - computer science , discretization , speedup , partial differential equation , convergence (economics) , multi core processor , measure (data warehouse) , hausdorff distance , nonlinear system , bottleneck , advection , numerical analysis , algorithm , mathematics , computational science , parallel computing , data mining , artificial intelligence , mathematical analysis , physics , quantum mechanics , economics , embedded system , economic growth , thermodynamics

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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