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Bias Field Estimation and Adaptive Segmentation of MRI Data Using a Modified Fuzzy C-Means Algorithm

Mohamed N. Ahmed, Sameh M. Yamany, Aly A. Farag, Thomas Moriarty
CVPR 1999 pp. 1250-1255
doi:10.1109/CVPR.1999.786947 /cvpr/1999/ahmed1999cvpr-bias/

Abstract

In this paper, we present a novel algorithm for adaptive fuzzy segmentation of MRI data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the RF coils or some problems associated with the acquisition sequences. The result is a slowly-varying shading artifact over the image that can produce errors with conventional intensity-based classification. Our algorithm is formulated by modifying the objective function of the standard fuzzy c-means (FCM) algorithm to compensate for such inhomogeneities and to allow the labeling of a pixel (voxel) to be influenced by the labels in its immediate neighborhood. The neighborhood effect acts as a regularizer and biases the solution towards piecewise-homogeneous labelings. Such a regularization is useful in segmenting scans corrupted by salt and pepper noise. Experimental results on both synthetic images and MR data are given to demonstrate the effectiveness and efficiency of the proposed algorithm.

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Cite

Text

Ahmed et al. "Bias Field Estimation and Adaptive Segmentation of MRI Data Using a Modified Fuzzy C-Means Algorithm." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999. doi:10.1109/CVPR.1999.786947

Markdown

[Ahmed et al. "Bias Field Estimation and Adaptive Segmentation of MRI Data Using a Modified Fuzzy C-Means Algorithm." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999.](https://mlanthology.org/cvpr/1999/ahmed1999cvpr-bias/) doi:10.1109/CVPR.1999.786947

BibTeX

@inproceedings{ahmed1999cvpr-bias,
  title     = {{Bias Field Estimation and Adaptive Segmentation of MRI Data Using a Modified Fuzzy C-Means Algorithm}},
  author    = {Ahmed, Mohamed N. and Yamany, Sameh M. and Farag, Aly A. and Moriarty, Thomas},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1999},
  pages     = {1250-1255},
  doi       = {10.1109/CVPR.1999.786947},
  url       = {https://mlanthology.org/cvpr/1999/ahmed1999cvpr-bias/}
}