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Multi-domain, Higher Order Level Set Scheme for 3D Image Segmentation on the GPU

Ojaswa Sharma, Qin Zhang, Francois Anton, Chandrajit Bajaj
DTU Informatics, The Technical University of Denmark, Denmark
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010, p.2211-2216

@conference{sharma2010multi,

   title={Multi-domain, higher order level set scheme for 3D image segmentation on the GPU},

   author={Sharma, O. and Zhang, Q. and Anton, F. and Bajaj, C.},

   booktitle={Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on},

   pages={2211–2216},

   issn={1063-6919},

   year={2010},

   organization={IEEE}

}

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Level set method based segmentation provides an efficient tool for topological and geometrical shape handling. Conventional level set surfaces are only C^0 continuous since the level set evolution involves linear interpolation to compute derivatives. Bajaj et al. present a higher order method to evaluate level set surfaces that are C^2 continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming solver is efficient in memory usage.
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