Three-dimensional reconstruction of the statistics of heterogeneous objects from a collection of one projection image of each object.
An estimation problem for statistical reconstruction of heterogeneous three-dimensional objects from two-dimensional tomographic data (single-particle cryoelectron microscope images) is posed as the problem of estimating class probabilities, means, and covariances for a Gaussian mixture where both the mean and covariance are stochastically structured. Both discrete (i.e., classes) and continuous heterogeneity is included. A maximum likelihood solution computed by a generalized expectation-maximization algorithm is presented and demonstrated on experimental images of Flock House Virus.
Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, USA.
Yili
Y
Zheng
Qiu
Q
Wang
Peter C
PC
Doerschuk
D000465:Algorithms; D020285:Cryoelectron Microscopy; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007304:Insect Viruses; D015233:Models, Statistical; D011336:Probability; D014054:Tomography