Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Compensation of Spatial Inhomogeneity in MRI Based on a Parametric Bias Estimate
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
An Extensible MRI Simulator for Post-Processing Evaluation
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Retrospective illumination correction of greyscale historical aerial photos
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
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This paper presents a method to suppress the bias artifact, also known as RF-inhomogeneity, in Magnetic Resonance Imaging (MRI). This artifact produces illumination variations due to magnetic field fluctuations of the device. In the latest years many works have been devoted to face this problem. In this work we present the 3D version of a new approach to bias correction, which is called Exponential Entropy Driven Homomorphic Unsharp Masking (E2D-HUM). This technique has been already presented by some of the authors for the 2D case only. The description of the whole method is detailed, and some experimental results are reported.