Application of rough set based dynamic parameter optimization to MRI segmentation

We introduce a multi-spectral MRI segmentation technique based on approximate reducts derived from the data mining paradigm of the theory of rough sets. We use genetic algorithms to tune the parameterized attributes and search for the best segmentation models based on approximate reducts.

[1]  Douglas L. Rickman,et al.  Validation of magnetic resonance imaging (MRI) multispectral tissue classification , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[2]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[3]  Thomas K. Pilgram,et al.  Validation of magnetic resonance imaging (MRI) multispectral tissue classification. , 1991, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[4]  Benoit M. Dawant,et al.  Morphometric analysis of white matter lesions in MR images: method and validation , 1994, IEEE Trans. Medical Imaging.

[5]  D. Louis Collins,et al.  Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images , 1995, IEEE Trans. Medical Imaging.

[6]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[7]  Vasken Kollokian,et al.  Performance analysis of automatic techniques for tissue classification in magnetic resonance images of the human brain , 1996 .

[8]  Jakub Wroblewski,et al.  Theoretical Foundations of Order-Based Genetic Algorithms , 1996, Fundam. Informaticae.

[9]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[10]  Andrzej Skowron,et al.  Rough Sets: A Tutorial , 1998 .

[11]  R. Kikinis,et al.  Automated segmentation of MR images of brain tumors. , 2001, Radiology.

[12]  Ron Kikinis,et al.  Automated Segmentation of MRI of Brain Tumors , 2001 .

[13]  Natasa Kovacevic,et al.  A Robust Method for Extraction and Automatic Segmentation of Brain Images , 2002, NeuroImage.

[14]  Alan C. Evans,et al.  Automatic Generation of Training Data for Brain Tissue Classification from MRI , 2002, MICCAI.

[15]  Dominik Slezak,et al.  Approximate Entropy Reducts , 2002, Fundam. Informaticae.

[16]  Rik Van de Walle,et al.  An integrated method of adaptive enhancement for unsupervised segmentation of MRI brain images , 2003, Pattern Recognit. Lett..

[17]  Dominik Slezak,et al.  Order Based Genetic Algorithms for the Search of Approximate Entropy Reducts , 2003, RSFDGrC.

[18]  Dominik Slezak.  The Rough Bayesian Model for Distributed Decision Systems , 2004, Rough Sets and Current Trends in Computing.

[19]  Kenneth Revett,et al.  An Automated Multi-spectral MRI Segmentation Algorithm Using Approximate Reducts , 2004, Rough Sets and Current Trends in Computing.