Paper
30 January 2012 Interactive 3D segmentation by tubular envelope model for the aorta treatment
Pawel J. Lubniewski, Bruno Miguel, Vincent Sauvage, Christophe Lohou
Author Affiliations +
Proceedings Volume 8290, Three-Dimensional Image Processing (3DIP) and Applications II; 82901F (2012) https://doi.org/10.1117/12.912069
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
We propose a novel interactive 3D segmentation approach and geometric model definition called tubular envelope model. It is conceived to express the shape of tubular objects. The main challenges we have achieved are the speed and interactivity of the construction. A computer program designed for this task gives the user full control of the shape and precision, with no significant computational errors. Six CT (computed tomography) aortic dissection images have been used for the tubular envelopes construction. Hence, we have proposed a generic parametric model of the aorta for its interactive construction. It leads us to rapid visualization and navigation inside the artery (rough virtual angioscopy). The low complexity of the model and the ease of interactive design makes the tubular envelope suitable for aorta segmentation in comparison to the other segmentation methods. The model accuracy is adjustable by the user according to his requirements; the time of construction is approved by clinicians. More generally, the tubular envelope could be used in other applications, e.g. to define a region of interest for more precise segmentation or feature extraction inside, to develop a parametric model with deformation capabilities.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pawel J. Lubniewski, Bruno Miguel, Vincent Sauvage, and Christophe Lohou "Interactive 3D segmentation by tubular envelope model for the aorta treatment", Proc. SPIE 8290, Three-Dimensional Image Processing (3DIP) and Applications II, 82901F (30 January 2012); https://doi.org/10.1117/12.912069
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Cited by 6 scholarly publications.
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KEYWORDS
Image segmentation

3D modeling

Arteries

Blood

Computed tomography

3D image processing

Visualization

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