TY - GEN
T1 - Automatically identifying white matter tracts using cortical labels
AU - Bogovic, John A.
AU - Carass, Aaron
AU - Wan, Jing
AU - Landman, Bennett A.
AU - Prince, Jerry L.
PY - 2008
Y1 - 2008
N2 - Diffusion tensor imaging (DTI) has become a standard clinical procedure in assessing the health of white matter in the brain. Tractography, the tracing of individual fibers in the brain using DTI data, has begun to play a more central role in neuroscience research, particularly in understanding the relationships between brain connectivity and behavior. The measuring of features related to bundles of fibers, i.e., tracts or fasciculi, is currently problematic because of the need for manual interaction. This article presents an algorithm for the automatic identification of selected white matter tracts. It extracts fibers using the FACT algorithm and finds cortical gyral labels using a multi-atlas deformable registration scheme. Tracts are identified as the fibers passing between selected cortical labels. The quality of automatic labels are compared both visually and numerically against a well-accepted manual approach. The automatic approach is shown to be more consistent with conventional definitions of tracts and more repeatable on separate scans of the same subject.
AB - Diffusion tensor imaging (DTI) has become a standard clinical procedure in assessing the health of white matter in the brain. Tractography, the tracing of individual fibers in the brain using DTI data, has begun to play a more central role in neuroscience research, particularly in understanding the relationships between brain connectivity and behavior. The measuring of features related to bundles of fibers, i.e., tracts or fasciculi, is currently problematic because of the need for manual interaction. This article presents an algorithm for the automatic identification of selected white matter tracts. It extracts fibers using the FACT algorithm and finds cortical gyral labels using a multi-atlas deformable registration scheme. Tracts are identified as the fibers passing between selected cortical labels. The quality of automatic labels are compared both visually and numerically against a well-accepted manual approach. The automatic approach is shown to be more consistent with conventional definitions of tracts and more repeatable on separate scans of the same subject.
KW - Image segmentation
KW - Magnetic resonance imaging
UR - http://www.scopus.com/inward/record.url?scp=51049084008&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51049084008&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2008.4541141
DO - 10.1109/ISBI.2008.4541141
M3 - Conference contribution
AN - SCOPUS:51049084008
SN - 9781424420032
T3 - 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI
SP - 895
EP - 898
BT - 2008 5th IEEE International Symposium on Biomedical Imaging
T2 - 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Y2 - 14 May 2008 through 17 May 2008
ER -