Nicolas Guizard

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Brain extraction is an important step in the analysis of brain images. The variability in brain morphology and the difference in intensity characteristics due to imaging sequences make the development of a general purpose brain extraction algorithm challenging. To address this issue, we propose a new robust method (BEaST) dedicated to produce consistent and(More)
BACKGROUND Adverse neurodevelopmental outcome is an important source of morbidity in children with congenital heart disease (CHD). A significant proportion of newborns with complex CHD have abnormalities of brain size, structure, or function, which suggests that antenatal factors may contribute to childhood neurodevelopmental morbidity. METHODS AND(More)
Cross-sectional analysis of longitudinal anatomical magnetic resonance imaging (MRI) data may be suboptimal as each dataset is analyzed independently. In this study, we evaluate how much variability can be reduced by analyzing structural volume changes in longitudinal data using longitudinal analysis. We propose a two-part pipeline that consists of(More)
OBJECTIVE The objective of the study was to characterize total and regional volumetric brain growth in healthy fetuses during the second and third trimesters of pregnancy, using an automated method. STUDY DESIGN We developed and validated an automated method to quantify global and regional in vivo brain volumes using fetal magnetic resonance imaging. We(More)
The cerebellum has recently been recognized for its role in high-order functions, including cognition, language, and behavior. Recent studies have also begun to describe a functional topography of the mature cerebellum that includes organization on a mediolateral axis. However, no study to date has examined the relationship between regional cerebellar(More)
Intracranial electrodes are sometimes implanted in patients with refractory epilepsy to identify epileptic foci and propagation. Maximal recording of EEG activity from regions suspected of seizure generation is paramount. However, the location of individual contacts cannot be considered with current manual planning approaches. We propose and validate a(More)
Template-based segmentation techniques have been developed to facilitate the accurate targeting of deep brain structures in patients with movement disorders. Three template-based brain MRI segmentation techniques were compared to determine the best strategy for segmenting the deep brain structures of patients with Parkinson’s disease. T1-weighted and(More)
Cerebellar injury is an important complication of preterm birth with far-reaching neuropsychiatric sequelae. We have previously shown a significant association between isolated injury to the premature cerebellum and subsequent impairment of regional volumetric growth in the contralateral cerebrum. In the current study, we examine the relationship between(More)
Multiple sclerosis (MS) lesion segmentation is crucial for evaluating disease burden, determining disease progression and measuring the impact of new clinical treatments. MS lesions can vary in size, location and intensity, making automatic segmentation challenging. In this paper, we propose a new supervised method to segment MS lesions from 3D magnetic(More)
Gray matter atrophy provides important insights into neurodegeneration in multiple sclerosis (MS) and can be used as a marker of neuroprotection in clinical trials. Jacobian integration is a method for measuring volume change that uses integration of the local Jacobian determinants of the nonlinear deformation field registering two images, and is a(More)