Back-Projection Reconstruction—CT and PET/SPECT

Author(s):  
Michael Chappell
1998 ◽  
Vol 45 (3) ◽  
pp. 1133-1137 ◽  
Author(s):  
T.H. Farquhar ◽  
A. Chatziioannou ◽  
G. Chinn ◽  
M. Dahlbom ◽  
E.J. Hoffman

2013 ◽  
Vol 749 ◽  
pp. 371-376
Author(s):  
Yang Xuan ◽  
Xu Wang ◽  
Cheng An Liu ◽  
Dan Yang

Magnetic induction tomography (MIT) is a noninvasive and contactless imaging modality which aims at the reconstruction of the electrical conductivity in objects from alternating magnetic fields. Filtered back projection reconstruction algorithm is widely used in biomedical imaging field, and tried to use in MIT. Finite element analysis model has been established based on Scharfetter coil-coil model and perturbation theory, then simulated coaxial coil system by ANSYS software, the perturbation aroused by a target object moving on vertical coil axis. The sensitivity of a target object moves in vacuum and a salt solution were calculated respectively, the characteristics of the perturbation sensitivity in a salt solution were analyzed. The conditions of filtered back projection reconstruction algorithm in MIT were discussed.


Author(s):  
Weiping Liu

To overcome the radiation damage in electron microscopy, the method of 3-D reconstruction from single exposure, random conical tilting series has been developed for single particles with one preferred orientation on the grid. Due to the high noise components in the projections which propagate to the 3-D reconstruction, there is the question about the reproducibility of individual features in the reconstruction. This question cannot be answered by a resolution estimation, because resolution describes the average reliability of the features across the 3-D reconstruction. Also when two independent reconstructions of related particles (e.g. labeled vs. unlabeled) are compared, the following questions are raised: could they have arisen from the same structure? where are the feature differences located? how reliable are the conclusions? These questions can be answered by estimating the variances of the 3-D reconstructions. Since for the random conical method, different projections correspond to different particles on the grid, the conformational differences of these particles can contribute a substantial and recurrent portion to the noise components of their projections. A 3-D variance map should also reveal the 3-D locations of such conformational changes.


2013 ◽  
Vol 72 (4) ◽  
pp. 1079-1086 ◽  
Author(s):  
Ioannis Koktzoglou ◽  
Charles A. Mistretta ◽  
Shivraman Giri ◽  
Eugene E. Dunkle ◽  
Parag Amin ◽  
...  

2013 ◽  
Vol 72 (3) ◽  
pp. 749-755 ◽  
Author(s):  
David Chen ◽  
Behzad Sharif ◽  
Rohan Dharmakumar ◽  
Louise E.J. Thomson ◽  
C. Noel Bairey Merz ◽  
...  

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