Model-Free automatic segmentation of the aortic valve in multislice computed tomography images
Küçük Resim Yok
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pamukkale Univ
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Aortic Valve, Segmentation, Model-Free, Region Growing, Hessian, Supravalvular Sinus Detection, Ascending Aorta, Computed Tomography, Valvular Heart Diseases
Kaynak
Pamukkale University Journal of Engineering Sciences-Pamukkale Universitesi Muhendislik Bilimleri Dergisi
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
27
Sayı
2
