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Cortico-subthalamic white matter tract strength predicts interindividual efficacy in stopping a motor responseA high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures.Revisiting brain atrophy and its relationship to disability in multiple sclerosisOpen Science CBS Neuroimaging Repository: Sharing ultra-high-field MR images of the brain.Multi-modal ultra-high resolution structural 7-Tesla MRI data repository.Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity.A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI.Digital homeomorphisms in deformable registration.Volumetric neuroimage analysis extensions for the MIPAV software packageThe Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software.A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions.Longitudinal multiple sclerosis lesion segmentation data resource.Reconstruction of the human cerebral cortex robust to white matter lesions: method and validation.BigBrain: an ultrahigh-resolution 3D human brain model.Development and evaluation of an algorithm for the computer-assisted segmentation of the human hypothalamus on 7-Tesla magnetic resonance imagesSimple paradigm for extra-cerebral tissue removal: algorithm and analysis.Direct segmentation of the major white matter tracts in diffusion tensor imagesConsistent segmentation using a Rician classifierAssessing intracortical myelin in the living human brain using myelinated cortical thicknessTopology correction of segmented medical images using a fast marching algorithm.Intensity standardisation of 7T MR images for intensity-based segmentation of the human hypothalamus.System for integrated neuroimaging analysis and processing of structure.Homeomorphic brain image segmentation with topological and statistical atlases.TOPOLOGY PRESERVING AUTOMATIC SEGMENTATION OF THE SPINAL CORD IN MAGNETIC RESONANCE IMAGESTract-specific quantitative MRI better correlates with disability than conventional MRI in multiple sclerosis.Estimation and application of spatially variable noise fields in diffusion tensor imaging.Mapping of the internal structure of human habenula with ex vivo MRI at 7T.Layer-specific intracortical connectivity revealed with diffusion MRI.Parametrization of white matter manifold-like structures using principal surfaces.Automated segmentation of the cerebellar lobules using boundary specific classification and evolution.Body Topography Parcellates Human Sensory and Motor Cortex.A Multiple Geometric Deformable Model Framework for Homeomorphic 3D Medical Image SegmentationTopology preserving tissue classification with fast marching and topology templates.Resolution of Crossing Fibers with Constrained Compressed Sensing using Traditional Diffusion Tensor MRI.Resolution of crossing fibers with constrained compressed sensing using diffusion tensor MRI.Topology-Preserving STAPLEDistance Transforms in Multi Channel MR Image Registration.Statistical Fusion of Surface Labels Provided by Multiple Raters.A Novel Contrast for DTI Visualization for Thalamus Delineation.Multi-contrast multi-scale surface registration for improved alignment of cortical areas.
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Q26722181-B3AD120B-F82B-48F5-A1DE-3450DA441464Q28648337-D37F5279-0FBB-47A8-B122-9C1E23426D70Q28729953-5784A926-E9AC-429F-9B42-BC651B8DE76CQ30488274-5CCC36B8-C0AF-4DD4-B604-1C412A521C90Q30648269-4A504DC5-196E-4D93-983D-EF5E4552B4A1Q30990564-2E22A505-4334-480E-AFEB-7AA3688F0BB4Q31004270-8A9D3B0C-03A7-4609-A416-36123180C3F2Q31119001-2E14C7DB-F577-400D-8843-8D7936E49518Q33289565-CAD74322-D702-49E9-B0D6-E12B9A316DA8Q33524433-AB8E9D5B-A825-4511-B970-0A71D7F9ADB0Q33590515-93064B63-4F8A-4264-B4C3-8BA58769215FQ33623433-5E53D3D9-64DE-495A-902A-DA9D19CA1C66Q33748381-E141296A-BDFF-45FB-8360-5D6D34EB45A6Q34352439-37D4A445-BD3E-475C-9DAD-C9206FEEE5E1Q34917581-629F84C5-2F9C-45B8-BB0F-68B9A64C4307Q35017061-6B70BD74-B3DF-4179-8C82-45BB2D109467Q35175855-C1D068A7-2848-4D2B-8054-2F396770E04FQ35705790-2A327EB6-5467-452D-9514-506F6DE42E16Q36191848-2300F5FE-D316-44C3-A9A4-50FEB62FB7B3Q36247770-553E6ABF-CC9C-4C15-898E-50BC7A7FF35CQ36295429-FCFB9382-6F3C-41DB-96FD-835A795E82B4Q36438030-33CFBB8E-8EEF-4C8B-BD94-A6B6D603E4C1Q36925089-F9E088CF-4BFA-4005-85EF-4543AC82431FQ36992694-E3E8306A-0E31-48C4-8812-84839F5226BCQ37120776-F5171B07-C220-4526-9415-F68A4D069F4CQ37322224-034541CD-BB20-4DC5-9F2C-D2F3329D18EFQ37408525-2AEEA1D5-1DB1-417D-8143-0AF35AB24EEDQ37464455-C2F7DDA7-73FC-4C86-A5B6-36D30AD0370CQ37577735-7C637B64-F3A1-45EB-B9CD-A8214E9CD1C7Q37692616-A1407B03-8303-421D-BB8C-9D80978FA2E8Q38968707-58C92DA3-3DED-4EF1-805B-5158016DC316Q39472770-DAF992D7-DC89-4A3A-8F49-953B808B7A0FQ39789502-16BA098B-C107-406B-9130-16B9DC86115DQ40015130-3240B2E7-B614-4166-B25F-7A50ED05197BQ40282391-5C75D20E-18F7-4438-AD03-51E314F22170Q40492778-93EB2AFF-34B3-410A-9BC4-61BEEB96CD88Q41155332-2EDAFC36-C456-4DD6-94F4-82D6D2E54AABQ41192200-8FC8397D-F247-407C-88DD-7833FCFADCF3Q41193717-32739398-1E8C-417A-A8F6-CA8F692683CCQ41443245-222AA9EB-7832-42D4-B20F-231C05C91F13
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description
onderzoeker
@nl
researcher
@en
հետազոտող
@hy
name
Pierre-Louis Bazin
@ast
Pierre-Louis Bazin
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Pierre-Louis Bazin
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Pierre-Louis Bazin
@nl
Pierre-Louis Bazin
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type
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Pierre-Louis Bazin
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Pierre-Louis Bazin
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Pierre-Louis Bazin
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Pierre-Louis Bazin
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Pierre-Louis Bazin
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prefLabel
Pierre-Louis Bazin
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Pierre-Louis Bazin
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Pierre-Louis Bazin
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Pierre-Louis Bazin
@nl
Pierre-Louis Bazin
@sl
P106
P2456
P31
P496
0000-0002-0141-5510