DocumentCode :
3463680
Title :
Multicomputer-based neural networks for imaging in random media
Author :
Schlereth, F.H. ; Fossaceca, J.M. ; Keckler, A.D. ; Barbour, R.L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
fYear :
1991
fDate :
2-9 Nov. 1991
Firstpage :
2193
Abstract :
The authors describe a novel technique for imaging in random media using a neural network approach based on a modified backpropagation algorithm. Simulation results indicate that it is possible to produce images of simple structures in 2-D media with a reasonable computation time. The present approach is computation-intensive and for this reason the authors have developed a machine architecture and a machine, Kilonode, which is well suited to this class of computing problems, and which can ultimately be produced at a cost which is suitable for commercial application of the neural network algorithms.<>
Keywords :
medical diagnostic computing; neural nets; 2D media; Kilonode; computing problems; imaging in random media; machine architecture; multicomputer-based neural networks; Absorption; Computer networks; Differential equations; Intelligent networks; Least squares approximation; Neural networks; Optical imaging; Optical scattering; Random media; Reconstruction algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1991., Conference Record of the 1991 IEEE
Conference_Location :
Santa Fe, NM, USA
Print_ISBN :
0-7803-0513-2
Type :
conf
DOI :
10.1109/NSSMIC.1991.259308
Filename :
259308
Link To Document :
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