Title :
Computed tomography based on a self-organizing neural network
Author :
Monma, Hiroaki ; Chen, Yen-wei ; Nakao, Zensho
Author_Institution :
Fac. of Eng., Ryukyus Univ., Okinawa, Japan
Abstract :
We propose a method based on a self-organizing neural network (SONN) for computed tomography (CT). An expectation maximization-maximum likelihood algorithm, which is a well-known method for CT, is used as a learning algorithm of the network. The network is trained to minimize the Euclidean distance between the obtained projections and the projections of the estimate. Since the SONN starts with many different estimates, it is easy to obtain a global optimum
Keywords :
computerised tomography; image reconstruction; learning (artificial intelligence); maximum likelihood estimation; self-organising feature maps; Euclidean distance; computed tomography; expectation maximization-maximum likelihood algorithm; global optimum; learning algorithm; self-organizing neural network; Computed tomography; Computer networks; Electronic mail; Euclidean distance; Image reconstruction; Iterative algorithms; Iterative methods; Neural networks; Neurons; Organizing;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.812528
