Volumetric feature extraction and visualization of tomographic molecular imaging.
Electron tomography is useful for studying large macromolecular complex within their cellular context. The associate problems include crowding and complexity. Data exploration and 3D visualization of complexes require rendering of tomograms as well as extraction of all features of interest. We present algorithms for fully automatic boundary segmentation and skeletonization, and demonstrate their applications in feature extraction and visualization of cell and molecular tomographic imaging. We also introduce an interactive volumetric exploration and visualization tool (Volume Rover), which encapsulates implementations of the above volumetric image processing algorithms, and additionally uses efficient multi-resolution interactive geometry and volume rendering techniques for interactive visualization.
Bajaj
Chandrajit
C
Department of Computer Sciences and Institute of Computational and Engineering Sciences, University of Texas at Austin, Austin, TX 78712, USA. bajaj@cs.utexas.edu
Yu
Zeyun
Z
Auer
Manfred
M
D000465:Algorithms; D016880:Anisotropy; D055592:Biophysical Phenomena; D001703:Biophysics; D004058:Diffusion; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D020407:Internet; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D011506:Proteins / Q000737:chemistry*; D012984:Software
D011506:Proteins