Modified fuzzy \(c\)-means algorithm for segmentation of T1-T2-weighted brain MRI

DOI10.1016/j.cam.2010.08.033zbMath1201.92042OpenAlexW2035640334MaRDI QIDQ611831

Sumit K. Garg

Publication date: 14 December 2010

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2010.08.033

zbMATH Keywords

clusteringdata analysissegmentationFCMmodified FCM

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Image analysis in multivariate analysis (62H35) Neural biology (92C20) Biomedical imaging and signal processing (92C55) Multivariate analysis and fuzziness (62H86)

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Improving the runtime of MRF based method for MRI brain segmentation

Cites Work

• A modified fuzzy \(C\)-means image segmentation algorithm for use with uneven illumination patterns
• Efficient Implementation of the Fuzzy c-Means Clustering Algorithms
• Convergence theory for fuzzy c-means: Counterexamples and repairs
• A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
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