eprintid: 2240
rev_number: 7
eprint_status: archive
userid: 6
dir: disk0/00/00/22/40
datestamp: 2014-07-03 10:05:28
lastmod: 2014-07-03 10:05:28
status_changed: 2014-07-03 10:05:28
type: book_section
metadata_visibility: show
creators_name: Unay, Devrim
creators_name: Harmankaya, Ibrahim
creators_name: Oksuz, Ilkay
creators_name: Kadipasaoglu, Kamuran
creators_name: Cubuk, Rahmi
creators_name: Celik, Levent
creators_id: 
creators_id: 
creators_id: ilkay.oksuz@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
title: Automated aortic supravalvular sinus detection in  conventional computed tomography image
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
keywords: Computed Tomography; Region growing; Segmentation;  Supravalvular sinus detection
note: 21st Signal Processing and Communications Applications Conference (SIU), Haspolat, Cypros, 24-26 April 2013 
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.
date: 2013-04
publisher: IEEE
pagerange: 1-4
event_title: Signal Processing and Communications Applications Conference (SIU), 2013 21st
id_number: 10.1109/SIU.2013.6531489
refereed: TRUE
isbn: 978-1-4673-5561-2 
book_title: Proceedings of the 21st Signal Processing and Communications Applications Conference (SIU)
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6531489&isnumber=6531159
citation:   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)