Real-Time Electron Tomography Based on GPU Computing

Electron tomography (ET) has emerged as the leading technique for the structural analysis of unique complex biological specimens. Recently, real-time ET systems have appeared on the scene and they combine the computer-assisted image collection with the 3D reconstruction, and provide the users a preliminary structure of the specimen. This rough structure allows the users to easily evaluate the quality of the specimen and decide whether a more time-consuming processing and thorough analysis of the dataset is worthwhile. The aim of this work is to develop software for real-time ET systems. The principle of ET is based upon 3D reconstruction from projections. By means of tomographic reconstruction algorithms, the projection images in the tilt series can then be combined to yield the 3D structure of the specimen. The 3D structure has poor signal to noise ratio, so it is necessary an additional non linear filtering process in order to achieve enough resolution. Then, Matrix Weighted Back Projections (Matrix WBP) and Beltrami methods have been selected as reconstruction and filter procedures, respectively. First the Matrix WBP is applied to the input sinograms to obtain the three-dimensional structure and, next, Beltrami filter de-noises the image. Both methods are highly accelerated by GPU platforms. The power of GPU computing is then exploited to further improve the performance and yield reconstructions of biological datasets in seconds, it allows to integrate both methods on real time electron tomography systems.