Paper
11 March 2008 Three-dimensional segmentation of bones from CT and MRI using fast level sets
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Abstract
Our task is to segment bones from 3D CT and MRI images. The main application is creation of 3D mesh models for finite element modeling. These surface and volume vector models can be used for further biomechanical processing and analysis. We selected a novel fast level set method because of its high computational efficiency, while preserving all advantages of traditional level set methods. Unlike in traditional level set methods, we are not solving partial differential equations (PDEs). Instead, the contours are represeted by two sets of points, corresponding to the inner and outer edge of the object boundary. We have extended the original implementation in 3D, where the speed advantage over classical level set segmentation are even more pronounced. We can segment a CT image of 512×512×125 in less than 20s by this method. It is approximately two orders of magnitude faster than standard narrow band algorithms. Our experiments with real 3D CT and MRI images presented in this paper showed high ability of the fast level set algorithm to solve complex segmentation problems.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jakub Kratky and Jan Kybic "Three-dimensional segmentation of bones from CT and MRI using fast level sets", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691447 (11 March 2008); https://doi.org/10.1117/12.770954
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Cited by 20 scholarly publications.
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KEYWORDS
Image segmentation

3D image processing

Magnetic resonance imaging

Computed tomography

3D modeling

Bone

Image processing algorithms and systems

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