An Overview of Medical Image Registration
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
Principal components analysis competitive learning
Neural Computation
On the discrete-time dynamics of the basic Hebbian neural network node
IEEE Transactions on Neural Networks
A support vector machine formulation to PCA analysis and its kernel version
IEEE Transactions on Neural Networks
Convergence analysis of a deterministic discrete time system of Oja's PCA learning algorithm
IEEE Transactions on Neural Networks
Rapid surface registration of 3D volumes using a neural network approach
Image and Vision Computing
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
Image registration by normalized mapping
Neurocomputing
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Medical image registration plays an important role in clinical diagnosis and therapy planning. This paper proposes an automatic method to register computed tomography (CT) and magnetic resonance (MR) brain images by using first principal directions of feature images. In this method, principal component analysis (PCA) neural network is used to calculate the first principal directions from feature images, then the registration is accomplished by simply aligning feature images' first principal directions and centroids. Simulations for MR-MR (MR and MR images) registration and CT-MR (CT and MR images) registration are carried out to illustrate the method.