Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Boundary Detection by Constrained Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained Restoration and the Recovery of Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A parametric gradient descent MRI intensity inhomogeneity correction algorithm
Pattern Recognition Letters
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Magnetic Resonance Images(MRI) are piecewise constant functions that can be corrupted by an inhomogeneous illumination field. We propose a gradient descent parametric illumination correction algorithm for MRI. The illumination bias is modelled as a linear combination of 2D products of Legendre polynomials. The error function is related to the classification error in the bias corrected image. In this work the intensity classes are given beforehand, so the adaptive algorithm is used only to estimate the bias field. We test our algorithm against Maximum A Posteriori algorithms over some images from the ISBR public domain database.