A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-Means

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[1]  Jerry L. Prince,et al.  Adaptive fuzzy segmentation of magnetic resonance images , 1999, IEEE Transactions on Medical Imaging.

[2]  Baowei Fei,et al.  A modified fuzzy C-means classification method using a multiscale diffusion filtering scheme , 2009, Medical Image Anal..

[3]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[4]  D. Louis Collins,et al.  A new improved version of the realistic digital brain phantom , 2006, NeuroImage.

[5]  Hesheng Wang,et al.  Multiscale fuzzy C-means image classification for multiple weighted MR images for the assessment of photodynamic therapy in mice , 2007, SPIE Medical Imaging.

[6]  R. Leahy,et al.  Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.

[7]  A. Evans,et al.  MRI simulation-based evaluation of image-processing and classification methods , 1999, IEEE Transactions on Medical Imaging.

[8]  Charles R. Meyer,et al.  Retrospective correction of intensity inhomogeneities in MRI , 1995, IEEE Trans. Medical Imaging.

[9]  Aly A. Farag,et al.  A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data , 2002, IEEE Transactions on Medical Imaging.

[10]  Martin Styner,et al.  Parametric estimate of intensity inhomogeneities applied to MRI , 2000, IEEE Transactions on Medical Imaging.

[11]  Ioannis Sechopoulos,et al.  Automatic tissue classification for high-resolution breast CT images based on bilateral filtering , 2011, Medical Imaging.