An automated string-based approach to extracting and characterizing White Matter fiber-bundles

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.

Source: Computers in Biology and Medicine - July 29, 2016 Category: Bioinformatics Authors: Francesco Cauteruccio, Claudio Stamile, Giorgio Terracina, Domenico Ursino, Dominique Sappey-Marinier Source Type: research