Abstract
In this paper a new scheme for automatic segmentation of the Aortic Valve in 3D computed tomography image sequences is presented. The algorithm is based on a new approach that uses a combination of Region Growing and Mathematical Morphology techniques in a hybrid framework. The output of the algorithm is used to assess the Aortic Valve Calcium Score in a new way that calculates the Agatston Score separately in both Sinuses and Leaflets, deriving a new index based on their ratios. Aortic Valve borders and leaflets identification is still a challenging task, and commonly based on intensive user interaction that limits its applicability. In this paper a fast and accurate model-free, automated method for segmenting and extracting morphological parameters with Score Calcium calculation is presented. Results of the proposed method are also provided showing a high correlation with the expected values.
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Torío, L. et al. (2016). A Hybrid Model for Extracting the Aortic Valve in 3D Computerized Tomography and Its Application to Calculate a New Calcium Score Index. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_77
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DOI: https://doi.org/10.1007/978-3-319-41501-7_77
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