An automated string-based approach to extracting and characterizing White Matter fiber-bundles. (1st October 2016) - Cauteruccio, Francesco; Stamile, Claudio; Terracina, Giorgio; Ursino, Domenico; Sappey-Marinier, Dominique
Abstract: In this paper, we propose an automated approach to extracting White Matter (WM) fiber-bundles through clustering and model characterization. The key novelties of our approach are: a new string-based formalism, allowing an alternative representation of WM fibers, a new string dissimilarity metric, a WM fiber clustering technique, and a new model-based characterization algorithm. Thanks to these novelties, the complex problem of WM fiber-bundle extraction and characterization reduces to a much simpler and well-known string extraction and analysis problem. Interestingly, while several past approaches extract fiber-bundles by grouping available fibers on the basis of provided atlases (and, therefore, cannot capture possibly existing fiber-bundles nor represented in the atlases), our approach first clusters available fibers once and for all, and then tries to associate obtained clusters with models provided directly and dynamically by users. This more dynamic and interactive way of proceeding can help the detection of fiber-bundles autonomously proposed by our approach and not present in the initial models provided by experts. Abstract : Highlights: Automated extraction of White Matter fiber-bundles. Characterization of White Matter fiber-bundles. A new string-based formalism for representing White Matter fiber-bundles. A new metric for handling possibly heterogeneous strings.