Unay, Devrim and Harmankaya, Ibrahim and Oksuz, Ilkay and Kadipasaoglu, Kamuran and Cubuk, Rahmi and Celik, Levent Automated aortic supravalvular sinus detection in conventional computed tomography image. In: Proceedings of the 21st Signal Processing and Communications Applications Conference (SIU). IEEE, pp. 1-4. ISBN 978-1-4673-5561-2 (2013)
Full text not available from this repository.Abstract
Valvular diseases are those where one or more of the cardiac valves are affected. Treatment of valvular diseases often involves replacement or restoration of the affected valve(s). In such a surgical procedure, the medical expert performing the procedure can largely benefit from a patient-specific and dynamic valvular model containing information complementary to the 2D/3D static images. To this end, in this study a novel automated supravalvular sinus detection method (to be used as a first step in aortic valve segmentation) on conventional contrast-enhanced ECG-gated multislice CT data and its evaluation on expert annotated 31 real cases are presented. Results demonstrate a highly accurate detection performance with average error rate inferior to 1.12 mm.
| Item Type: | Book Section |
|---|---|
| Identification Number: | https://doi.org/10.1109/SIU.2013.6531489 |
| Additional Information: | 21st Signal Processing and Communications Applications Conference (SIU), Haspolat, Cypros, 24-26 April 2013 |
| Uncontrolled Keywords: | Computed Tomography; Region growing; Segmentation; Supravalvular sinus detection |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Ms T. Iannizzi |
| Date Deposited: | 03 Jul 2014 10:05 |
| Last Modified: | 03 Jul 2014 10:05 |
| URI: | http://eprints.imtlucca.it/id/eprint/2240 |
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