Evento
Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays
Tipo del evento:
Conferencia
Nombre del evento:
31st Conference on Neural Information Processing Systems
Fecha del evento:
04/12/2017
Institución Organizadora:
National Science Foundation;
Título de la revista:
Neural Information Processing
Editorial:
Neural Information Processing Systems Foundation
ISSN:
1738-2572
Idioma:
Inglés
Clasificación temática:
Resumen
Recently, linear formulations and convex optimization methods have been proposed to predict diffusion-weighted Magnetic Resonance Imaging (dMRI) data given estimates of brain connections generated using tractography algorithms. The size of the linear models comprising such methods grows with both dMRI data and connectome resolution, and can become very large when applied to modern data. In this paper, we introduce a method to encode dMRI signals and large connectomes, i.e., those that range from hundreds of thousands to millions of fascicles (bundles of neuronal axons), by using a sparse tensor decomposition. We show that this tensor decomposition accurately approximates the Linear Fascicle Evaluation (LiFE) model, one of the recently developed linear models. We provide a theoretical analysis of the accuracy of the sparse decomposed model, LiFE_SD, and demonstrate that it can reduce the size of the model significantly. Also, we develop algorithms to implement the optimization solver using the tensor representation in an efficient way.
Palabras clave:
Multiway arrays
,
Diffusion Imaging
,
Tensor Decomposition
,
Tractography
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Eventos(IAR)
Eventos de INST.ARG.DE RADIOASTRONOMIA (I)
Eventos de INST.ARG.DE RADIOASTRONOMIA (I)
Citación
Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays; 31st Conference on Neural Information Processing Systems; Long Beach; Estados Unidos; 2017; 1-11
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