1063

Interactive, GPU-Based Level Sets for 3D Segmentation

Aaron Lefohn, Joshua Cates, Ross Whitaker
School of Computing, University of Utah
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2003 (2003), pp. 564-572.

@article{lefohn2003interactive,

   title={Interactive, gpu-based level sets for 3d segmentation},

   author={Lefohn, A. and Cates, J. and Whitaker, R.},

   journal={Medical Image Computing and Computer-Assisted Intervention-MICCAI 2003},

   pages={564–572},

   year={2003},

   publisher={Springer}

}

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While level sets have demonstrated a great potential for 3D medical image segmentation, their usefulness has been limited by two problems. First, 3D level sets are relatively slow to compute. Second, their formulation usually entails several free parameters which can be very difficult to correctly tune for specific applications. This paper presents a tool for 3D segmentation that relies on level-set surface models computed at interactive rates on commodity graphics cards (GPUs). The interactive rates for solving the level-set PDE give the user immediate feedback on the parameter settings, and thus users can tune three separate parameters and control the shape of the model in real time. We have found that this interactivity enables users to produce good, reliable segmentation, as supported by qualitative and quantitative results.
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