DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection. Export

@article{citeulike:459009, abstract = {Several approaches have been used to trace axonal trajectories from diffusion MRI data. If such techniques were first developed in a deterministic framework reducing the diffusion information to one single main direction, more recent approaches emerged that were statistical in nature and that took into account the whole diffusion information. Based on diffusion tensor MRI data coming from normal brains, this paper presents how brain connectivity could be modelled globally by means of a random walk algorithm. The mass of connections thus generated was then virtually dissected to uncover different tracts. Corticospinal, corticobulbar, and corticothalamic tracts, the corpus callosum, the limbic system, several cortical association bundles, the cerebellar peduncles, and the medial lemniscus were all investigated. The results were then displayed in the form of an in vivo brain connectivity atlas. The connectivity pattern and the individual fibre tracts were then compared to known anatomical data; a good matching was found.}, address = {Signal Processing Institute, Swiss Federal Institute of Technology, 1015 Lausanne, Switzerland. patric.hagmann@epfl.ch}, author = {Hagmann, P. and Thiran, J. P. and Jonasson, L. and Vandergheynst, P. and Clarke, S. and Maeder, P. and Meuli, R.}, citeulike-article-id = {459009}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/12880786}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=12880786}, issn = {1053-8119}, journal = {Neuroimage}, keywords = {connectivity, dti, mri, vivo}, month = {July}, number = {3}, pages = {545--554}, posted-at = {2008-10-16 13:19:33}, priority = {2}, title = {DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/12880786}, volume = {19}, year = {2003} }

TY - JOUR ID - citeulike:459009 L3 - citeulike-article-id:459009 N2 - Several approaches have been used to trace axonal trajectories from diffusion MRI data. If such techniques were first developed in a deterministic framework reducing the diffusion information to one single main direction, more recent approaches emerged that were statistical in nature and that took into account the whole diffusion information. Based on diffusion tensor MRI data coming from normal brains, this paper presents how brain connectivity could be modelled globally by means of a random walk algorithm. The mass of connections thus generated was then virtually dissected to uncover different tracts. Corticospinal, corticobulbar, and corticothalamic tracts, the corpus callosum, the limbic system, several cortical association bundles, the cerebellar peduncles, and the medial lemniscus were all investigated. The results were then displayed in the form of an in vivo brain connectivity atlas. The connectivity pattern and the individual fibre tracts were then compared to known anatomical data; a good matching was found. IS - 3 JF - Neuroimage SN - 1053-8119 AD - Signal Processing Institute, Swiss Federal Institute of Technology, 1015 Lausanne, Switzerland. patric.hagmann@epfl.ch EP - 554 TI - DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection. VL - 19 SP - 545 KW - connectivity KW - dti KW - mri KW - vivo AU - Hagmann, P AU - Thiran, JP AU - Jonasson, L AU - Vandergheynst, P AU - Clarke, S AU - Maeder, P AU - Meuli, R PY - 2003/07// UR - http://view.ncbi.nlm.nih.gov/pubmed/12880786 ER -