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• W2077688032 abstract "We have developed an automated segmentation method for three-dimensional vascular ultrasound images. The method consists of two steps: an automated initial contour identification, followed by application of a geometrically deformable model (GDM). The formation of the initial contours requires the input of a single seed point by the user, and was shown to be insensitive to the placement of the seed within a structure. The GDM minimizes contour energy, providing a smoothed final result. It requires only three simple parameters, all with easily selectable values. The algorithm is fast, performing segmentation on a 336 x 352 x 200 volume in 25 s when running on a 100 MHz 9500 Power Macintosh prototype. The segmentation algorithm was tested on stenosed vessel phantoms with known geometry, and the segmentation of the cross-sectional areas was found to be within 3% of the true area. The algorithm was also applied to two sets of patient carotid images, one acquired with a mechanical scanner and the other with a freehand scanning system, with good results on both." @default.
• W2077688032 created "2016-06-24" @default.
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• W2077688032 date "2001-03-21" @default.
• W2077688032 modified "2023-10-16" @default.
• W2077688032 title "An automated segmentation method for three-dimensional carotid ultrasound images" @default.
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• W2077688032 doi "https://doi.org/10.1088/0031-9155/46/4/327" @default.
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