Jean-Christophe Souplet

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Processing and visualization of 3D medical data is nowadays a common problem. However, it remains challenging because the diversification and complexification of the available sources of information, as well as the specific requirements of clinicians, make it difficult to solve in a computer science point of view. Indeed, clinicians need ergonomic,(More)
Automatic brain MRI segmentations methods are useful but computationally intensive tools in medical image computing. Deploying them on grid infrastructures can provide an efficient resource for data handling and computing power. In this study, an efficient implementation of a brain MRI segmentation method through a grid-interfaced workflow enactor is(More)
The aim of this PhD thesis is to analyse a database of multiple sclerosis<lb>(MS) brain magnetic resonance images (MRI). For this purpose, two biomarkers have<lb>been selected (lesion load and brain atrophy). They can be evaluated manually by<lb>the physician. However, manual measurements are a fastidious task and are subject<lb>to interand intraexpert(More)
In multiple sclerosis (MS) research, burden of disease and treatments efficacy are mainly evaluated with lesion load and atrophy. The former being poorly correlated with patient’s handicap, it is of interest to evaluate accurately the latter. A lot of methods to measure the brain atrophy are available in the literature. The brain parenchymal fraction (BPF)(More)
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