Oct 1, 2016 · In this paper, we propose an automated approach to extracting White Matter (WM) fiber-bundles through clustering and model characterization.
This work reduces the complex problem of White Matter fiber clustering to a much simpler and well-known string clustering problem and can be extended to ...
In this paper, we propose an automated approach to extracting White Matter (WM) fiber-bundles through clustering and model characterization. The key novelties ...
In this paper, we propose an automated approach to extracting White Matter (WM) fiber-bundles through clustering and model characterization.
An automated string-based approach to extracting and characterizing White Matter fiber-bundles. F. Cauteruccio , C. Stamile , G. Terracina , D. Ursino ...
Indeed, the usage of a string-based model, representing the shape of a particular fiber-bundle, allows an easy extraction of just those fibers having the same ...
A model-guided approach to extracting anatomically plausible White Matter fiber-bundles from the high number of streamlines generated by tractography ...
An automated string-based approach to extracting and ... - dblp
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Bibliographic details on An automated string-based approach to extracting and characterizing White Matter fiber-bundles.
This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans.
An automated string-based approach to extracting and characterizing White Matter fiber-bundles. Cauteruccio F;Stamile C;Terracina G;Ursino D;Sappey-Marinier ...