CT image reconstruction by back-propagation

Author

Nakao, Zensho ; Ali, F.E.A.F. ; Chen, Yen-wei

Author_Institution

Fac. of Eng., Ryukyus Univ., Okinawa, Japan

Volume

2

fYear

1997

fDate

27-23 May 1997

Firstpage

323

Abstract

A neural network model is used in CT image reconstruction from four projections. The system is based on the backpropagation algorithm for adaptation of connection weights. Satisfactory agreement between the original and reconstructed images was obtained in simulation, and the results obtained are compared to those obtained by the well-known algebraic reconstruction technique (ART), and it was found that the neural network method is more effective than ART when the number of projection directions is very limited

Keywords

backpropagation; computerised tomography; feedforward neural nets; image reconstruction; multilayer perceptrons; CT image reconstruction; algebraic reconstruction technique; backpropagation; computerised tomography; connection weight adaptation; multilayer perceptron; neural network model; projection directions; simulation; Computational modeling; Computed tomography; Genetic algorithms; Image reconstruction; Intelligent systems; Inverse problems; Iterative methods; Neural networks; Simulated annealing; Subspace constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-3755-7

Type

conf

DOI

10.1109/KES.1997.619404

Filename

619404