This Medical Image Computing and Computer Assisted Intervention (MICCAI) 2003 paper by Lefohn et al. describes a brain tumor segmentation study performed with a new GPU-based level-set solver. This paper demonstrates that the ability to interact with a level-set computation in real time enables users to quickly produce segmentations from MRI data that qualitatively and quantitatively compare favorably with expert hand-segmentations. (Interactive, GPU-Based Level Sets for 3D Brain Tumor Segmentation. Aaron E. Lefohn, Joshua E. Cates and Ross T. Whitaker. To appear at “Medical Image Computing and Computer Assisted Intervention,” (MICCAI) 2003.)

This paper by Lefohn et. al. at the University of Utah demonstrates a 3D level-set PDE solver implemented entirely on an ATI Radeon 8500 GPU. It shows that in addition to the basic level-set equations, the second-order mean curvature speed term can be successfully evaluated with only 8-bit textures. The paper demonstrates the solver segmenting the cortical surface from a 256 x 256 x 175 MRI volume and compares the results to a CPU implementation. The object oriented framework with which the solver was built, “Glift,” is also discussed. (A GPU-Based, Three-Dimensional Level Set Solver with Curvature Flow. Aaron Lefohn and Ross Whitaker. University of Utah tech report UUCS-02-017, December, 2002.)