FPGA-based forward and back-projection operators for tomographic reconstruction

2013 ◽  
Author(s):  
Kyungchan Jin ◽  
Sangyup Song
Keyword(s):  
Tomographic Reconstruction ◽  
Projection Operators ◽  
Back Projection

scholarly journals Choquet integrals as projection operators for quantified tomographic reconstruction

2009 ◽  
Vol 160 (2) ◽  
pp. 198-211 ◽  
Author(s):  
Agnès Rico ◽  
Olivier Strauss ◽  
Denis Mariano-Goulart
Keyword(s):  
Tomographic Reconstruction ◽  
Projection Operators ◽  
Choquet Integrals

Fast projection/backprojection and incremental methods applied to synchrotron light tomographic reconstruction

2018 ◽  
Vol 25 (1) ◽  
pp. 248-256
Author(s):  
Camila de Lima ◽  
Elias Salomão Helou
Keyword(s):  
Projection Operator ◽  
Tomographic Reconstruction ◽  
Computational Cost ◽  
Iterative Algorithms ◽  
Incremental Algorithm ◽  
Back Projection ◽  
Tomographic Images ◽  
Incremental Methods ◽  
Order Of Magnitude ◽  
Synchrotron Light

Iterative methods for tomographic image reconstruction have the computational cost of each iteration dominated by the computation of the (back)projection operator, which take roughlyO(N3) floating point operations (flops) forN×Npixels images. Furthermore, classical iterative algorithms may take too many iterations in order to achieve acceptable images, thereby making the use of these techniques unpractical for high-resolution images. Techniques have been developed in the literature in order to reduce the computational cost of the (back)projection operator toO(N2logN) flops. Also, incremental algorithms have been devised that reduce by an order of magnitude the number of iterations required to achieve acceptable images. The present paper introduces an incremental algorithm with a cost ofO(N2logN) flops per iteration and applies it to the reconstruction of very large tomographic images obtained from synchrotron light illuminated data.

scholarly journals Rapid Method for Electron Tomographic Reconstruction and Three-Dimensional Modeling of the Murine Synapse Using an Automated Fiducial Marker-Free System

2013 ◽  
Vol 19 (S5) ◽  
pp. 182-187 ◽  
Author(s):  
Hyun-wook Kim ◽  
Seung Hak Oh ◽  
Namkug Kim ◽  
Eiko Nakazawa ◽  
Im Joo Rhyu
Keyword(s):  
Electron Tomography ◽  
Tomographic Reconstruction ◽  
Three Dimensional ◽  
3D Models ◽  
Three Dimension ◽  
Synaptic Organization ◽  
Back Projection ◽  
Virtual Image ◽  
Free System ◽  
Three Dimensional Modeling

AbstractElectron tomography (ET) has recently afforded new insights into neuronal architecture. However, the tedious process of sample preparation, image acquisition, alignment, back projection, and additional segmentation process of ET repels beginners. We have tried Hitachi's commercial packages integrated with a Hitachi H-7650 TEM to examine the potential of using an automated fiducial-less approach for our own neuroscience research. Semi-thick sections (200–300 nm) were cut from blocks of fixed mouse (C57BL) cerebellum and prepared for ET. Sets of images were collected automatically as each section was tilted by 2° increments (±60°). “Virtual” image volumes were computationally reconstructed in three dimension (3D) with the EMIP software using either the commonly used “weighted back-projection” (WBP) method or “topography-based reconstruction” (TBR) algorithm for comparison. Computed tomograms using the TBR were more precisely reconstructed compared with the WBP method. Following reconstruction, the image volumes were imported into the 3D editing software A-View and segmented according to synaptic organization. The detailed synaptic components were revealed by very thin virtual image slices; 3D models of synapse structure could be constructed efficiently. Overall, this simplified system provided us with a graspable tool for pursuing ET studies in neuroscience.

Matrix Weighted Back-Projection Accelerates Tomographic Reconstruction

2008 ◽  
Author(s):  
E. Vicente ◽  
J. I. Agulleiro ◽  
E. M. Garzón ◽  
J. J. Fernández
Keyword(s):  
Tomographic Reconstruction ◽  
Back Projection
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