Jérémy Lecoeur

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Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain(More)
BACKGROUND Advances in white matter tractography enhance neurosurgical planning and glioma resection, but white matter tractography is limited by biological variables such as edema, mass effect, and tract infiltration or selection biases related to regions of interest or fractional anisotropy values. OBJECTIVE To provide an automated tract identification(More)
Accurate anatomic co-registration is a prerequisite for identifying structural and functional changes in longitudinal studies of brain plasticity. Current MRI methods permit collection of brain images across multiple scales, ranging from whole brain at relatively low resolution (≥1 mm), to local brain areas at the level of cortical layers and columns (∼100(More)
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