Shape modelling for tract selection.
Med Image Comput Comput Assist Interv
; 12(Pt 2): 150-7, 2009.
Article
en En
| MEDLINE
| ID: mdl-20426107
Probabilistic tractography provides estimates of the probability of a structural connection between points or regions in a brain volume, based on information from diffusion MRI. The ability to estimate the uncertainty associated with reconstructed pathways is valuable, but noise in the image data leads to premature termination or erroneous trajectories in sampled streamlines. In this work we describe automated methods, based on a probabilistic model of tract shape variability between individuals, which can be applied to select seed points in order to maximise consistency in tract segmentation; and to discard streamlines which are unlikely to belong to the tract of interest. Our method is shown to ameliorate false positives and remove the widely observed falloff in connection probability with distance from the seed region due to noise, two important problems in the tractography literature. Moreover, the need to apply an arbitrary threshold to connection probability maps is entirely obviated by our approach, thus removing a significant user-specified parameter from the tractography pipeline.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Encéfalo
/
Reconocimiento de Normas Patrones Automatizadas
/
Interpretación de Imagen Asistida por Computador
/
Imagenología Tridimensional
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Imagen de Difusión Tensora
/
Modelos Anatómicos
/
Fibras Nerviosas Mielínicas
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Med Image Comput Comput Assist Interv
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
/
INFORMATICA MEDICA
Año:
2009
Tipo del documento:
Article
Pais de publicación:
Alemania