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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Off-line determination of the optimal number of iterations of the robust anisotropic diffusion filter applied to denoising of brain MR images

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Autor(es):
Ferrari, Ricardo J. [1]
Número total de Autores: 1
Afiliação do(s) autor(es):
[1] Univ Fed Sao Carlos, Dept Comp Sci, BR-13565905 Sao Carlos, SP - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING; v. 51, n. 1-2, p. 71-88, FEB 2013.
Citações Web of Science: 10
Resumo

Although anisotropic diffusion filters have been used extensively and with great success in medical image denoising, one limitation of this iterative approach, when used on fully automatic medical image processing schemes, is that the quality of the resulting denoised image is highly dependent on the number of iterations of the algorithm. Using many iterations may excessively blur the edges of the anatomical structures, while a few may not be enough to remove the undesirable noise. In this work, a mathematical model is proposed to automatically determine the number of iterations of the robust anisotropic diffusion filter applied to the problem of denoising three common human brain magnetic resonance (MR) images (T1-weighted, T2-weighted and proton density). The model is determined off-line by means of the maximization of the mean structural similarity index, which is used in this work as metric for quantitative assessment of the resulting processed images obtained after each iteration of the algorithm. After determining the model parameters, the optimal number of iterations of the algorithm is easily determined without requiring any extra computation time. The proposed method was tested on 3D synthetic and clinical human brain MR images and the results of qualitative and quantitative evaluation have shown its effectiveness. (AU)

Processo FAPESP: 12/03100-3 - Pesquisa e desenvolvimento de técnicas automáticas para a detecção, segmentação e análise de placas de esclerose múltipla em imagens de ressonância magnética
Beneficiário:Ricardo José Ferrari
Linha de fomento: Auxílio à Pesquisa - Regular
Processo FAPESP: 08/09050-2 - Pesquisa e desenvolvimento de técnicas automáticas para a detecção e medição volumétrica de placas de esclerose múltipla
Beneficiário:Ricardo José Ferrari
Linha de fomento: Auxílio à Pesquisa - Apoio a Jovens Pesquisadores