TY  - CHAP
SN  - 978-1-4673-5561-2 
EP  - 4
PB  - IEEE
Y1  - 2013/04//
SP  - 1
A1  - Unay, Devrim
A1  - Harmankaya, Ibrahim
A1  - Oksuz, Ilkay
A1  - Kadipasaoglu, Kamuran
A1  - Cubuk, Rahmi
A1  - Celik, Levent
T2  - Proceedings of the 21st Signal Processing and Communications Applications Conference (SIU)
AV  - none
ID  - eprints2240
TI  - Automated aortic supravalvular sinus detection in  conventional computed tomography image
N1  - 21st Signal Processing and Communications Applications Conference (SIU), Haspolat, Cypros, 24-26 April 2013 
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6531489&isnumber=6531159
N2  - 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.
KW  - Computed Tomography; Region growing; Segmentation;  Supravalvular sinus detection
ER  -