Ultra-fast Tomographic Reconstruction with a Highly Optimized Weighted Back-Projection Algorithm

Abstract

Electron tomography (ET) allows elucidation of the three-dimensional (3D) structure of large complex biological specimens at molecular resolution. In order to achieve such resolution levels, large projection images have to be used to compute the 3D reconstructions. Tomographic reconstruction on this scale requires a tremendous use of computational resources and a considerable processing time. In this work, we present and evaluate a highly optimized implementation of the Weighted Back-Projection reconstruction algorithm. Briefly, optimizations made to the code comprise (1) vector processing with SSE (Streaming SIMD Extensions) instructions, (2) an efficient use of cache memory, (3) to take advantage of the inherent image symmetry, (4) to use the FFTW (Fastest Fourier Transform in the West) library for image filtering, (5) to use regions of interest and last, but not least, (6) a wide range of minor optimizations like some data pre-calculations or an instruction level parallelism improvement. We have evaluated the method on tomographic reconstructions of several datasets and on two computing platforms. The results show that our version speeds up the method by a factor around 14 or 16, depending on the platform.