Medical image analysis, 2013-10, Vol.17 (7), p.844-857
2013
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- Autor(en) / Beteiligte
- Titel
- Tractometer: Towards validation of tractography pipelines
- Ist Teil von
- Medical image analysis, 2013-10, Vol.17 (7), p.844-857
- Ort / Verlag
- Netherlands: Elsevier B.V
- Erscheinungsjahr
- 2013
- Quelle
- MEDLINE
- Beschreibungen/Notizen
- [Display omitted] •New online system to evaluate tractography pipelines.•New connectivity-based quantitative measures (valid and invalid bundles/connections and average bundle coverage).•More than 57,000 different combinations of tractography pipelines compared from the FiberCup dataset.•Take-home messages for tractography users and insights on remaining open questions for the community. We have developed the Tractometer: an online evaluation and validation system for tractography processing pipelines. One can now evaluate the results of more than 57,000 fiber tracking outputs using different acquisition settings (b-value, averaging), different local estimation techniques (tensor, q-ball, spherical deconvolution) and different tracking parameters (masking, seeding, maximum curvature, step size). At this stage, the system is solely based on a revised FiberCup analysis, but we hope that the community will get involved and provide us with new phantoms, new algorithms, third party libraries and new geometrical metrics, to name a few. We believe that the new connectivity analysis and tractography characteristics proposed can highlight limits of the algorithms and contribute in solving open questions in fiber tracking: from raw data to connectivity analysis. Overall, we show that (i) averaging improves quality of tractography, (ii) sharp angular ODF profiles helps tractography, (iii) seeding and multi-seeding has a large impact on tractography outputs and must be used with care, and (iv) deterministic tractography produces less invalid tracts which leads to better connectivity results than probabilistic tractography.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1361-8415eISSN: 1361-8423DOI: 10.1016/j.media.2013.03.009Titel-ID: cdi_proquest_miscellaneous_1399057057
- Format
- –
- Schlagworte
- a-ODF, ABC, Algorithms, Analytical Orientation Distribution Function (ODF), Artificial Intelligence, Average Bundle Coverage, Brain - cytology, Cerebral Spinal Fluid, Cingulum, Connectivity analysis, Constant Solid Angle ODF, Corpus Callosum, Corticospinal Tract, csa-ODF, CSF, CST, diffusion Magnetic Resonance Imaging, Diffusion MRI, Diffusion Tensor Imaging, Diffusion Tensor Imaging - methods, Diffusion Weighted Imaging, dMRI, DTI, DWI, Fiber ODF, fODF, Fractional Anisotropy, Grey Matter, HARDI, High Angular Resolution Diffusion Imaging, Humans, Image Enhancement - methods, Image Interpretation, Computer-Assisted - methods, Imaging, Three-Dimensional - methods, Internet, Invalid Bundles, Invalid Connections, maximal SH order 6, Nerve Fibers, Myelinated - ultrastructure, No Connections, ODF, Online Systems, Orientation Distribution Function, Pattern Recognition, Automated - methods, Region Of Interest, Reproducibility of Results, ROI, Runge–Kutta, SD-r6, Sensitivity and Specificity, SLF, Software, Spherical Deconvolution of maximal SH order 6 (r6), Superior Longitudinal Fasciculus, TEND, Tensor Advection, Tractography, Valid Bundles, Valid Connections, Validation, White Matter