Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications
type: Item
instance of: scholarly article
title: Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications
zbMATH Open document ID: 1343.49053
author: Quang Tung Thieu
author: Marie Luong
author: Jean-Marie Rocchisani
author: Nikolay Metodiev Sirakov
author: Emmanuel Viennet
published in: Annals of Mathematics and Artificial Intelligence
publication date: 2015-10-06T00:00:00Z
Mathematics Subject Classification ID: 49M30
Mathematics Subject Classification ID: 65D10
Mathematics Subject Classification ID: 65K10
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 68U10
Mathematics Subject Classification ID: 92C55
zbMATH DE Number: 6489792
zbMATH Keywords: image segmentation
zbMATH Keywords: fuzzy energy function
zbMATH Keywords: local-global fuzzy Gaussian distribution
zbMATH Keywords: intensity inhomogeneity
zbMATH Keywords: convexity
zbMATH Keywords: confidence intervals
zbMATH Keywords: medical imaging
MaRDI profile type: Publication
full work available at URL: s10472-014-9413-y
OpenAlex ID: W2004285853
cites work: Q3969900
cites work: A geometric model for active contours in image processing
cites work: Active contours without edges
cites work: Fuzzy Energy-Based Active Contours
cites work: A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
cites work: Segmentation by a Local and Global Fuzzy Gaussian Distribution Energy Minimization of an Active Contour Model
cites work: Active contours driven by local Gaussian distribution fitting energy
cites work: An efficient local Chan-Vese model for image segmentation
DOI: 10.1007/S10472-014-9413-Y
description: scientific article; zbMATH DE number 6489792