Structure and View Estimation for Tomographic Reconstruction: A Bayesian Approach

This paper addresses the problem of reconstructing the density of a scene from multiple projection images produced by modalities such as x-ray, electron microscopy, etc. where an image value is related to the integral of the scene density along a 3D line segment between a radiation source and a point on the image plane. While computed tomography (CT) addresses this problem when the absolute orientation of the image plane and radiation source directions are known, this paper addresses the problem when the orientations are unknown ? it is akin to the structure-from-motion (SFM) problem when the extrinsic camera parameters are unknown. We study the problem within the context of reconstructing the density of protein macro-molecules in Cryogenic Electron Microscopy (cryo-EM), where images are very noisy and existing techniques use several thousands of images. In a non-degenerate configuration, the viewing planes corresponding to two projections, intersect in a line in 3D. Using the geometr...

• Type: Conference
• Year: 2006
• Where: CVPR
• Authors: Satya P. Mallick, Sameer Agarwal, David J. Kriegman, Serge J. Belongie, Bridget Carragher, Clinton S. Potter
• Keywords: Computer Vision, Cryo-em Images, Cryogenic Electron Microscopy, CVPR 2006, Electron Micrograph Analysis, Image Plane, Line Correspondences