Title :
Automatic ultrastructure segmentation of reconstructed CryoEM maps of icosahedral viruses
Author :
Yu, Zeyun ; Bajaj, Chandrajit
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas, Austin, TX, USA
Abstract :
We present an automatic algorithm to segment all the local and global asymmetric units of a three-dimensional density map of icosahedral viruses. This approach is readily applicable to the structural analysis of a broad range of virus structures that are reconstructed using cryo-electron microscopy (cryo-EM) technique. Our algorithm includes three major steps operating on the three dimensional density map: the detection of critical points of the volumetric density function, the detection of global and local symmetry axes, and, finally, the boundary segmentation of all the asymmetric units. We demonstrate the efficacy of our algorithm and report our results on several experimental volumetric datasets, consisting of both reconstructed cryo-EM molecular density maps taken from the European Bioinformatics Institute archive, as well our own synthetically generated (blurred) maps calculated from X-ray resolution molecular structural data taken from the Protein Data Bank.
Keywords :
axial symmetry; electron microscopy; microorganisms; molecular biophysics; X-ray resolution molecular structural data; automatic ultrastructure segmentation; icosahedral viruses; reconstructed cryo-electron microscopy maps; symmetry axes; virus structure; Bioinformatics; Cells (biology); DNA; Microscopy; Nuclear magnetic resonance; Pathogens; Proteins; RNA; Viruses (medical); X-ray diffraction; Cryo-electron microscopy (cryo-EM) maps; icosahedral virus; segmentation; structure analysis; symmetry detection; three-dimensional (3-D) reconstruction; Algorithms; Artificial Intelligence; Cryoelectron Microscopy; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Viruses;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2005.852770