Paper
21 May 1999 Development and evaluation of a semiautomatic 3D segmentation technique of the carotid arteries from 3D ultrasound images
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Abstract
In this paper, we report on a semi-automatic approach to segmentation of carotid arteries from 3D ultrasound (US) images. Our method uses a deformable model which first is rapidly inflated to approximately find the boundary of the artery, then is further deformed using image-based forces to better localize the boundary. An operator is required to initialize the model by selecting a position in the 3D US image, which is within the carotid vessel. Since the choice of position is user-defined, and therefore arbitrary, there is an inherent variability in the position and shape of the final segmented boundary. We have assessed the performance of our segmentation method by examining the local variability in boundary shape as the initial selected position is varied in a freehand 3D US image of a human carotid bifurcation. Our results indicate that high variability in boundary position occurs in regions where either the segmented boundary is highly curved, or the 3D US image has poorly defined vessel edges.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jeremy D. Gill, Hanif M. Ladak, David A. Steinman, and Aaron Fenster "Development and evaluation of a semiautomatic 3D segmentation technique of the carotid arteries from 3D ultrasound images", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348576
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Image segmentation

3D image processing

3D modeling

Arteries

Ultrasonography

3D acquisition

3D metrology

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