A Robust Contextual Fuzzy C-Means Clustering Algorithm for Noisy Image Segmentation-Reference-Cited by-同舟云学术

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A Robust Contextual Fuzzy C-Means Clustering Algorithm for Noisy Image Segmentation

Published:2023-08-09 Issue:3 Volume:40 Page:488-512
ISSN:0176-4268
Container-title:Journal of Classification
language:en
Short-container-title:J Classif

Author:

Kalti Karim^ORCID,Touil Asma

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Psychology (miscellaneous),Mathematics (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s00357-023-09443-1.pdf

Reference37 articles.

1. Adhikari, S. K., Sing, J. K., Basu, D. K., & Nasipuri, M. (2015). Conditional spatial fuzzy c-means clustering algorithm for segmentation of MRI images. Applied Soft Computing, 34, 758–769.

2. Ahmed, M. N., Yamany, S. M., Mohamed, N., Farag, A. A., & Moriarty, T. (2002). A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Transactions on Medical Imaging, 21(3), 193–199.

3. Alruwaili, M., Siddiqi, M. H., & Javed, M. A. (2020). A robust clustering algorithm using spatial fuzzy c-means for brain MR images. Egyptian Informatics Journal, 21(1), 51–66.

4. Ayech, M. W., El Kalti, K., and El Ayeb, B. (2010) “Image segmentation based on adaptive fuzzy-c-means clustering." In 2010 20th International Conference on Pattern Recognition, 2306–2309. IEEE

5. Bezdek, J. C., Ehrlich, R., & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences, 10(2–3), 191–203.

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1. Accelerated Sequential Data Clustering;Journal of Classification;2024-05-09

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