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Performance evaluation of vessel extraction algorithm applied to Aortic root segmentation in CT Angiography
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 Title & Authors
Performance evaluation of vessel extraction algorithm applied to Aortic root segmentation in CT Angiography
Kim, Tae-Hyong; Hwang, Young-sang; Shin, Ki-Young;
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World Health Organization reported that heart-related diseases such as coronary artery stenoses show the highest occurrence rate which may cause heart attack. Using Computed Tomography angiography images will allow radiologists to detect and have intervention by creating 3D roadmapping of the vessels. However, it is often complex and difficult do reconstruct 3D vessel which causes very large amount of time and previous researches were studied to segment vessels more accurate automatically. Therefore, in this paper, Region Competition, Geodesic Active Contour (GAC), Multi-atlas based segmentation and Active Shape Model algorithms were applied to segment aortic root from CTA images and the results were analyzed by using mean Hausdorff distance, volume to volume measure, computational time, user-interaction and coronary ostium detection rate. As a result, Extracted 3D aortic model using GAC showed the highest accuracy but also showed highest user-interaction results. Therefore, it is important to improve automatic segmentation algorithm in future
Aortic root;Computer-aided detection (CAD);Computed tomography angiography (CTA);Three-dimensional vessel segmentation;Geodesic Active Contour (GAC);
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