期刊
IEEE TRANSACTIONS ON MEDICAL IMAGING
卷 27, 期 9, 页码 1268-1274出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2008.922191
关键词
bootstrap; diffusion tensor; probabilistic; tractography; wild bootstrap
Diffusion tensor magnetic resonance imaging (DT-MRI) permits the noninvasive assessment of tissue microstructure and, with fibre-tracking algorithms, allows for the 3-D trajectories of white matter fasciculi to be reconstructed noninvasively. Probabilistic algorithms allow one to assign a confidence to a given reconstructed pathway-but often rely on a priori assumptions about sources of uncertainty in the data. Bootstrap methods have been proposed as a way of circum venting this problem, deriving the uncertainty from the data themselves-but acquisition times for data amenable to precise and robust bootstrapping are clinically prohibitive. By combining the wild bootstrap, recently introduced to the DT-MRI literature, with tractography, we show how confidence can be assigned to reconstructed trajectories using data collected in a fraction of the time required for regular bootstrapping. We compare in vivo wild bootstrap tracking results with regular tracking results and show that results are comparable. This approach therefore allows users who have collected data sets for use with deterministic tracking algorithms, rather than those specifically designed for bootstrapping, to be able to apply bootstrap analyses and retrospectively assign confidence to their reconstructed trajectories with minimum additional effort.
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