Relaxation methods for image reconstruction
Communications of the ACM
A Primal-Dual Method for Large-Scale Image Reconstruction in Emission Tomography
SIAM Journal on Optimization
Journal of Parallel and Distributed Computing
Anisotropic Nonlinear Filtering of Cellular Structures in Cryoelectron Tomography
Computing in Science and Engineering
Component-Averaged Row Projections: A Robust, Block-Parallel Scheme for Sparse Linear Systems
SIAM Journal on Scientific Computing
ACM Transactions on Mathematical Software (TOMS)
International Journal of High Performance Computing Applications
Energy-efficient deadline scheduling for heterogeneous systems
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
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Electron tomography (ET) combines electron microscopy and the principles of tomographic imaging in order to reconstruct the three-dimensional structure of complex biological specimens at molecular resolution. Weighted back-projection (WBP) has long been the method of choice since the reconstructions are very fast. It is well known that iterative methods produce better images, but at a very costly time penalty. In this work, it is shown that efficient parallel implementations of iterative methods, based primarily on data decomposition, can speed up such methods to an extent that they become viable alternatives to WBP. Precomputation of the coefficient matrix has also turned out to be important to substantially improve the performance regardless of the number of processors used. Matrix precomputation has made it possible to speed up the block-iterative component averaging (BICAV) algorithm, which has been studied before in the context of computerized tomography (CT) and ET, by a factor of more than 3.7. Component-averaged row projections (CARP) is a recently introduced block-parallel algorithm, which was shown to be a robust method for solving sparse systems arising from partial differential equations. It is shown that this algorithm is also suitable for single-axis ET, and is advantageous over BICAV both in terms of runtime and image quality. The experiments were carried out on several datasets of ET of various sizes, using the blob model for representing the reconstructed object.