In this paper, we present a method for the automated detection of lumen and media–adventitia border in intravascular ultrasound (IVUS) images. The method is based on nonparametric deformable models for accurate IVUS image segmentation.The proposed method is evaluated using 50 IVUS frames from 10 patients. The obtained results demonstrate that our method is statistically accurate and capable to identify boundaries automatically. In IVUS images Calcified deposits appear as bright echoes between two detected borders and obstruct the penetration of ultrasound, a phenomenon known as “acoustic shadowing.”We visualized the segmented frames and highlighted the calcified regions in the 3D representation of IVUS images.
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In this paper, we present a method for the automated detection of lumen and media–adventitia border in intravascular ultrasound (IVUS) images. The method is based on nonparametric deformable models for accurate IVUS image segmentation.The proposed method is evaluated using 50 IVUS frames from 10 patients. The obtained results demonstrate that our method is statistically accurate and capable to identify boundaries automatically. In IVUS images Calcified deposits appear as bright echoes between tw...
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