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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.)

Initialization of deformable models in 3D magnetic resonance images guided by automatically detected phase congruency point landmarks

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Autor(es):
Villa Pinto, Carlos H. [1] ; Ferrari, Ricardo Jose [1]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Fed Univ Sao Carlos UFSCar, Bip Grp, Dept Comp, BR-13565905 Sao Carlos, SP - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: PATTERN RECOGNITION LETTERS; v. 79, p. 1-7, AUG 1 2016.
Citações Web of Science: 2
Resumo

Deformable models are a widely used approach for 3D medical image segmentation, due to its flexibility and capability to incorporate prior anatomical knowledge in the segmentation process. However, methods based on deformable models are, usually, very sensitive to initialization, requiring that the initial position and shape of the model are as close as possible to the structure of interest in the target image. Thus, we propose in this work a novel approach for automatic initialization of deformable models for 3D MR images, using a set of automatically detected point landmarks to guide the process. Our approach combines 3D phase congruency based landmark detection, shape context based descriptors, nearest neighbor search and multilevel non-rigid B-spline transform estimation. A freely available atlas of 3D triangular meshes of brain structures, aligned to a reference image, is used as source for models. Our approach was tested in the initialization of models representing the corpus callosum (CC), left hippocampus (LH) and right hippocampus (RH). Results have shown a significant increase in the Jaccard and Dice metrics after the models were initialized by our method. (C) 2016 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 14/11988-0 - Desenvolvimento de um atlas probabilístico de pontos salientes 3D automaticamente detectados em imagens de ressonância magnética com aplicação no posicionamento inicial de modelos geométricos deformáveis
Beneficiário:Carlos Henrique Villa Pinto
Linha de fomento: Bolsas no Brasil - Mestrado
Processo FAPESP: 15/02232-1 - Segmentação automática de imagens de ressonância magnética do cérebro humano via modelos deformáveis guiados por atlas probabilístico de pontos salientes 3D
Beneficiário:Ricardo José Ferrari
Linha de fomento: Auxílio à Pesquisa - Regular