Title :
A supervised learning approach to landmark-based elastic biomedical image registration and interpolation
Author :
Wachowiak, Mark P. ; Smolikovà, Renata ; Zurada, Jacek M. ; Elmaghraby, Adel S.
Author_Institution :
Comput. Sci. & Eng. Program, Louisville Univ., KY, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
Biomedical image registration often requires local elastic matching after initial global alignment. Due to their universal approximation property, neural networks may be used for landmark-based elastic registration. A supervised learning approach using backpropagation, Bayesian regularization, Gauss-sigmoid networks, and radial basis function networks is presented for 2D elastic registration
Keywords :
backpropagation; belief networks; biomedical imaging; image registration; interpolation; radial basis function networks; Bayesian regularization; Gauss-sigmoid networks; backpropagation; interpolation; landmark-based elastic biomedical image registration; radial basis function networks; supervised learning approach; universal approximation property; Backpropagation; Bayesian methods; Biomedical engineering; Biomedical imaging; Computer science; Gaussian processes; Interpolation; Polynomials; Radial basis function networks; Supervised learning;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007761
