Abstract
A novel model-based identification of white brain matter in OCT A-scans is proposed. Based on nonlinear energy operators used in the classification of neural activity, candidates for white matter structures are extracted from a baseline-corrected signal. Validation of candidates is done by evaluating the correspondence to a simplified intensity model which is parametrized beforehand. Results for identification of white matter in rat brain in vitro show the capability of the proposed algorithm.
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CITATION STYLE
Ramrath, L., Hofmann, U. G., Huettmann, G., Moser, A., & Schweikard, A. (2007). Towards automated OCT-based identification of white brain matter. In Informatik aktuell (pp. 414–418). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-540-71091-2_83
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