Coronary Lumen Segmentation Using Graph Cuts and Robust Kernel Regression
| Autor: | Schaap, M., Neefjes, L., Metz, C., Giessen, A., Weustink, A., Mollet, N., Wentzel, J., Walsum, T. W., Wiro Niessen |
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| Přispěvatelé: | Medical Informatics, Cardiothoracic Surgery, Radiology & Nuclear Medicine, Cardiology |
| Rok vydání: | 2009 |
| Zdroj: | Lecture Notes in Computer Science, 5636, 528-539. Springer-Verlag Scopus-Elsevier |
| ISSN: | 0302-9743 |
| Popis: | This paper presents a novel method for segmenting the coronary lumen in CTA data. The method is based on graph cuts, with edge-weights depending on the intensity of the centerline, and robust kernel regression. A quantitative evaluation in 28 coronary arteries from 12 patients is performed by comparing the semi-automatic segmentations to manual annotations. This evaluation showed that the method was able to segment the coronary arteries with high accuracy, compared to manually annotated segmentations, which is reflected in a Dice coefficient of 0.85 and average symmetric surface distance of 0.22 mm. |
| Databáze: | OpenAIRE |
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