Three Dimensional Reconstruction From Limited Projection Data Using a Novel MART Algorithm

1999 ◽  
Author(s):  
Debasish Mishra ◽  
K. Muralidhar ◽  
P. Munshi

Abstract The present work is concerned with the development of a robust three dimensional reconstruction algorithm for applications involving tomography. In an earlier study it was shown that among the ART family of algorithms the multiplicative algebraic reconstruction algorithm (MART) was the most appropriate for tomographic reconstruction. In the present work, the MART algorithm has been extended so that (a) its performance is acceptable over a wider range of relaxation factors, (b) the time requirement for convergence to a solution is lower and (c) its performance is less sensitive to noise in the projection data. Two applications have been considered for evaluating the proposed algorithms namely a circular region with holes and experimental data recorded in a differentially heated fluid layer using an interferometer. The algorithms proposed are seen to be clearly an improvement over those presently available.

Author(s):  
J. Frank ◽  
B. F. McEwen ◽  
M. Radermacher ◽  
C. L. Rieder

The tomographic reconstruction from multiple projections of cellular components, within a thick section, offers a way of visualizing and quantifying their three-dimensional (3D) structure. However, asymmetric objects require as many views from the widest tilt range as possible; otherwise the reconstruction may be uninterpretable. Even if not for geometric obstructions, the increasing pathway of electrons, as the tilt angle is increased, poses the ultimate upper limitation to the projection range. With the maximum tilt angle being fixed, the only way to improve the faithfulness of the reconstruction is by changing the mode of the tilting from single-axis to conical; a point within the object projected with a tilt angle of 60° and a full 360° azimuthal range is then reconstructed as a slightly elliptic (axis ratio 1.2 : 1) sphere.


2020 ◽  
Vol 47 (1) ◽  
pp. 0110004
Author(s):  
刘爱林 Liu Ailin ◽  
张敬金 Zhang Jingjin ◽  
李思宁 Li Sining ◽  
孙剑峰 Sun Jianfeng ◽  
牛丽红 Niu Lihong ◽  
...  

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