Aort kapakçığının çok-kesitli bilgisayarlı tomografi görüntülerinden model-bağimsiz otomatik bölütlenmesi

Year 2021, Volume: 27 Issue: 2, 122 - 128, 04.04.2021

Devrim Ünay İbrahim Harmankaya İlkay Öksüz , Rahmi Çubuk Levent Çelik Kamuran Kadıpaşaoğlu

Abstract

Bir veya birden fazla kalp kapakçığının etkilenebildiği kapakçık hastalıklarının etkin tedavisi için bu kapakçıkların onarılması ya da değiştirilmesini gereklidir. Kapakçıkların 2B/3B statik görüntülerinden elde edilecek bilgiyi tamamlayıcı bilgi içeren hastaya-özgü ve dinamik bir model bu girişimsel tedavi rehberlik edebilir. Bu amaçla bu çalışmada yeni bir otomatik model-bağımsız aort kapakçığı bölütleme yöntemi önerilmiş ve yöntemin doğruluğu aort kapakçığının kapalı anına ait geleneksel kontrastlı EKG-güdümlü çok-kesitli BT verisinden elde edilen uzman işaretlemeleri ile ölçülmüştür. Yöntemin başarısı 19 gerçek veride detaylı olarak değerlendirilmiş ve Hessian temelli sonucun üzerine bölge büyütme yaklaşımının performansının umut vadettiği ama bunun yanı sıra problemin zorluğunu göstermiştir.

Keywords

Aort kapakçığı, Bölütleme, Model-Bağımsız, Bölge büyütme, Hessian, Supravalvüler sinüs tespiti, Çıkan aort, Bilgisayarlı tomografi, Kalp kapakçığı hastalıkları

Model-Free automatic segmentation of the aortic valve in multislice computed tomography images

Abstract

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.

Keywords

Aortic valve, Segmentation, Model-Free, Region growing, Hessian, Supravalvular sinus detection, Ascending aorta, Computed tomography, Valvular heart diseases

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