244-4 An Advanced Bayesian Algorithm for Multiphase Segmentation of 3-D X-Ray Micro Computed Tomography Data of Porous Materials.



Tuesday, October 18, 2011: 1:35 PM
Henry Gonzalez Convention Center, Room 006A, River Level

Markus Tuller, Soil, Water and Environmental Science, University of Arizona, Tucson, AZ and Ramaprasad Kulkarni, Electrical and Computer Engineering, University of Arizona, Tucson, AZ
An advanced Bayesian image classification algorithm based on Markov Random Fields will be introduced. The algorithm can be directly applied to segment reconstructed multiphase data of porous materials. This eliminates the need for dual-energy or wet/dry scans and associated image alignment and subtraction analysis that are commonly applied in synchrotron Micro-CT. To speed up segmentation of large 3-D datasets (i.e. 4000 x 4000 x 1000 voxels) the code is implemented in CUDA to utilize GPU parallel processing power. Applications to glass bead and soil data are shown and discussed.
See more from this Division: S01 Soil Physics
See more from this Session: General Soil Physics: I