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Diffusion-weighted imaging (DWI) enables non-invasive investigation and characterization of the white matter but suffers from a relatively poor spatial resolution. Increasing the spatial resolution in DWI is challenging with a single-shot EPI acquisition due to the decreased signal-to-noise ratio and T2(∗) relaxation effect amplified with increased echo(More)
We propose to carry out cooperatively both tissue and structure segmentations by distributing a set of local and cooperative models in a unified MRF framework. Tissue segmentation is performed by partitionning the volume into subvolumes where local MRFs are estimated in cooperation with their neighbors to ensure consistency. Local estimation fits precisely(More)
RATIONALE AND OBJECTIVES Tuberous sclerosis complex (TSC) is a genetic neurocutaneous syndrome in which cognitive and social-behavioral outcomes for patients vary widely in an unpredictable manner. The cause of adverse neurologic outcome remains unclear. The aim of this study was to investigate the hypothesis that disordered white matter and abnormal neural(More)
The problem addressed in this paper is the automatic segmentation of stroke lesions on MR multi-sequences. Lesions enhance differently depending on the MR modality and there is an obvious gain in trying to account for various sources of information in a single procedure. To this aim, we propose a multimodal Markov random field model which includes all MR(More)
The characterization of the complex diffusion signal arising from the brain remains an open problem. Many representations focus on characterizing the global shape of the diffusion profile at each voxel and are limited to the assessment of connectivity. In contrast, Multiple Fascicle Models (MFM) seek to represent the contribution from each white matter(More)
In most approaches, tissue and subcortical structure segmentations of MR brain scans are handled globally over the entire brain volume through two relatively independent sequential steps. We propose a fully Bayesian joint model that integrates local tissue and structure segmentations and local intensity distributions. It is based on the specification of(More)
Rapid and efficient imaging of the brain to monitor brain activity and neural connectivity is performed through functional MRI and diffusion tensor imaging (DTI) using the Echo-planar imaging (EPI) sequence. An entire volume of the brain is imaged by EPI in a few seconds through the measurement of all k-space lines within one repetition time. However, this(More)
Diffusion weighted imaging (DWI) is sensitive to alterations in the diffusion of water molecules caused by microstructural barriers. Different microstructural compartments are characterized by differences in DWI signal. Diffusion tensor imaging conflates the signal from these compartments into a single tensor, which poorly represents multiple white matter(More)
The purpose of this study was to examine the relationship between language pathways and autism spectrum disorders (ASDs) in patients with tuberous sclerosis complex (TSC). An advanced diffusion-weighted magnetic resonance imaging (MRI) was performed on 42 patients with TSC and 42 age-matched controls. Using a validated automatic method, white matter(More)
Accurate tissue and structure segmentation of magnetic resonance (MR) brain scans is critical in several applications. In most approaches this task is handled through two sequential steps. We propose to carry out cooperatively both tissue and subcortical structure segmentation by distributing a set of local and cooperative Markov random field (MRF) models(More)