A CASE ANALYSIS OF THE IMPACT OF PRIOR CENTER OF GRAVITY ESTIMATION OVER SKULL-STRIPPING ALGORITHMS IN MR IMAGES
Nenhuma Miniatura disponível
Data
2013-01-01
Autores
Miranda, Paulo André Vechiatto de [UNIFESP]
Cappabianco, Fabio Augusto Menocci [UNIFESP]
Ide, Jaime Shinsuke [UNIFESP]
IEEE
Orientadores
Tipo
Trabalho apresentado em evento
Título da Revista
ISSN da Revista
Título de Volume
Resumo
In this work, we propose a novel approach for improving center of gravity (COG) estimation of the brain in magnetic resonance (MR) images, that uses 3D Haar-like features. We hypothesize that better pose estimation will advance the posterior skull-stripping results of the popular Brain Extraction Tool (BET). The proposed methodology is quantitatively validated in 20 T1- and T2-weighted images of the brain. As compared to the native BET COG algorithm, our method produced COGs 87.3 % closer to the expected coordinates for the T1-weighted dataset, and importantly this resulted in an average enhancement of 15.4 % to the accuracy of skull-stripping masks. As far the authors know, we are first in analyzing the impact of COG estimation over skull-stripping of MR images.
Descrição
Citação
2013 20th Ieee International Conference On Image Processing (icip 2013). New York: Ieee, p. 675-679, 2013.