@inproceedings{7b3790450c9b41b993702a96a3f21e1f,
title = "Bilgisayarli tomografi g{\"o}r{\"u}nt{\"u}lerinde otomatik aortik kapak{\"u}st{\"u} b{\"o}lgesi tanimlama",
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.",
keywords = "Computed tomography, Region growing, Segmentation, Supravalvular sinus detection",
author = "Devrim {\"U}nay and Ibrahim Harmankaya and Ilkay {\"O}ks{\"u}z and Kamuran Kadipasaoglu and Rahmi {\c C}ubuk and Levent {\c C}elik",
year = "2013",
doi = "10.1109/SIU.2013.6531489",
language = "T{\"u}rk{\c c}e",
isbn = "9781467355629",
series = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013",
booktitle = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013",
note = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013 ; Conference date: 24-04-2013 Through 26-04-2013",
}