HIPS: A new hippocampus subfield segmentation method.
Neuroimage
; 163: 286-295, 2017 12.
Article
en En
| MEDLINE
| ID: mdl-28958881
ABSTRACT
The importance of the hippocampus in the study of several neurodegenerative diseases such as Alzheimer's disease makes it a structure of great interest in neuroimaging. However, few segmentation methods have been proposed to measure its subfields due to its complex structure and the lack of high resolution magnetic resonance (MR) data. In this work, we present a new pipeline for automatic hippocampus subfield segmentation using two available hippocampus subfield delineation protocols that can work with both high and standard resolution data. The proposed method is based on multi-atlas label fusion technology that benefits from a novel multi-contrast patch match search process (using high resolution T1-weighted and T2-weighted images). The proposed method also includes as post-processing a new neural network-based error correction step to minimize systematic segmentation errors. The method has been evaluated on both high and standard resolution images and compared to other state-of-the-art methods showing better results in terms of accuracy and execution time.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Imagen por Resonancia Magnética
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Interpretación de Imagen Asistida por Computador
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Neuroimagen
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Hipocampo
Límite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Neuroimage
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2017
Tipo del documento:
Article