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.
| Original language | English |
|---|---|
| Title of host publication | Bildverarbeitung für die Medizin 2007 |
| Editors | Alexander Horsch, Thomas M. Deserno, Heinz Handels, Hans-Peter Meinzer, Thomas Tolxdorff |
| Number of pages | 5 |
| Place of Publication | Berlin, Heidelberg |
| Publisher | Springer Berlin Heidelberg |
| Publication date | 2007 |
| Pages | 414-418 |
| ISBN (Print) | 978-3-540-71090-5 |
| ISBN (Electronic) | 978-3-540-71091-2 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | Workshop on Bildverarbeitung fur die Medizin 2007 - Munich, Germany Duration: 25.03.2007 → 27.03.2007 Conference number: 97564 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 10 Reduced Inequalities
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