NABS: non-local automatic brain hemisphere segmentation.
Magn Reson Imaging
; 33(4): 474-84, 2015 May.
Article
en En
| MEDLINE
| ID: mdl-25660644
ABSTRACT
In this paper, we propose an automatic method to segment the five main brain sub-regions (i.e. left/right hemispheres, left/right cerebellum and brainstem) from magnetic resonance images. The proposed method uses a library of pre-labeled brain images in a stereotactic space in combination with a non-local label fusion scheme for segmentation. The main novelty of the proposed method is the use of a multi-label block-wise label fusion strategy specifically designed to deal with the classification of main brain sub-volumes that process only specific parts of the brain images significantly reducing the computational burden. The proposed method has been quantitatively evaluated against manual segmentations. The evaluation showed that the proposed method was faster while producing more accurate segmentations than a current state-of-the-art method. We also present evidences suggesting that the proposed method was more robust against brain pathologies than the compared method. Finally, we demonstrate the clinical value of our method compared to the state-of-the-art approach in terms of the asymmetry quantification in Alzheimer's disease.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Reconocimiento de Normas Patrones Automatizadas
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Imagen por Resonancia Magnética
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Interpretación de Imagen Asistida por Computador
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Aumento de la Imagen
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Técnica de Sustracción
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Cerebro
Tipo de estudio:
Diagnostic_studies
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Guideline
Límite:
Humans
Idioma:
En
Revista:
Magn Reson Imaging
Año:
2015
Tipo del documento:
Article