Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications

DOI10.1007/S10472-014-9413-YzbMath1343.49053OpenAlexW2004285853MaRDI QIDQ499733

Quang Tung Thieu, Marie Luong, Jean-Marie Rocchisani, Nikolay Metodiev Sirakov, Emmanuel Viennet

Publication date: 6 October 2015

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-014-9413-y

zbMATH Keywords

confidence intervalsconvexitymedical imagingimage segmentationfuzzy energy functionintensity inhomogeneitylocal-global fuzzy Gaussian distribution

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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Clifford algebra multivectors and kernels for melanoma classification ⋮ Active contour directed by the Poisson gradient vector field and edge tracking

Cites Work

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• A geometric model for active contours in image processing
• Active contours driven by local Gaussian distribution fitting energy
• An efficient local Chan-Vese model for image segmentation
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• Segmentation by a Local and Global Fuzzy Gaussian Distribution Energy Minimization of an Active Contour Model
• Fuzzy Energy-Based Active Contours
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

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