title: Automatic feature extraction and statistical shape model of the AIDS virus spike.
abstract: We introduce a method to automatically extract spike features of the AIDS virus imaged through an electron microscope. The AIDS virus spike is the primary target of drug design as it is directly involved in infecting host cells. Our method detects the location of these spikes and extracts a subvolume enclosing the spike. We have achieved a sensitivity of 80% for our best operating range. The extracted spikes are further aligned and combined to build a 4-D statistical shape model, where each voxel in the shape model is assigned a probability density function. Our method is the first fully automated technique that can extract subvolumes of the AIDS virus spike and be used to build a statistical model without the need for any user supervision. We envision that this new tool will significantly enhance the overall process of shape analysis of the AIDS virus spike imaged through the electron microscope. Accurate models of the virus spike will help in the development of better drug design strategies.
authors.affiliation: LightLab Imaging, Inc., Westford, MA 01886, USA. ajay.gopinath@utexas.edu
authors.forename: Ajay
authors.initials: A
authors.lastname: Gopinath
authors.forename: Alan Conard
authors.initials: AC
authors.lastname: Bovik
mesh_terms: D000465:Algorithms; D015497:HIV-1 / Q000302:isolation & purification / Q000648:ultrastructure*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008854:Microscopy, Electron / Q000379:methods; D008954:Models, Biological; D015233:Models, Statistical; D012372:ROC Curve; D015302:Simian Immunodeficiency Virus / Q000648:ultrastructure