Yazar "Harmankaya, Ibrahim" seçeneğine göre listele

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    Automated Aortic Supravalvular Sinus Detection in Conventional Computed Tomography Image
    (IEEE, 2013) Unay, Devrim; Harmankaya, Ibrahim; Oksuz, Ilkay; Kadipasaoglu, Kamuran; Cubuk, Rahmi; Celik, Levent
    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.
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    Model-Free automatic segmentation of the aortic valve in multislice computed tomography images
    (Pamukkale Univ, 2021) Unay, Devrim; Harmankaya, Ibrahim; Oksuz, Ilkay; Çubuk, Rahmi; Çelik, Levent; Kadipasaoğlu, Kamuran
    Valvular diseases may affect one or more of the cardiac valves, which may need to be replaced or restored for effective treatment. The surgical procedure can be guided by a patient-specific and dynamic model containing information complementary to the 2D/3D static images of the valves. To this end, in this study a novel automated model-free aortic valve segmentation method is presented, and its performance is evaluated against expert annotations over conventional contrast-enhanced ECG-gated multislice CT data of the aortic valve at its closed position. Detailed evaluation of the proposed method in 19 real cases revealed an encouraging performance of 3D region growing over Hessian based approach but also demonstrated the complexity of the problem.