Automatic MR brain image segmentation using a multiseed based multiobjective clustering approach

Applied Intelligence

Volumn 35, Issue 3, 2011, Pages 411-427

  Saha, Sriparna ^a   Bandyopadhyay, Sanghamitra ^b  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Cluster validity measures; Clustering; Multiobjective optimization (MOO); Pareto optimal front; Simulated annealing (SA); Symmetry

Indexed keywords

AUTOMATIC CLUSTERING; AUTOMATIC SEGMENTATIONS; BRAIN IMAGES; CLUSTER VALIDITY INDICES; CLUSTER VALIDITY MEASURES; CLUSTERING; CLUSTERING PROBLEMS; CLUSTERING TECHNIQUES; DISTANCE-BASED; EUCLIDEAN DISTANCE; EXPECTATION MAXIMIZATION; FUZZY C MEAN; GROUND TRUTH; HYPERSPHERICAL; MAGNETIC RESONANCE BRAIN IMAGES; MAGNETIC RESONANCE IMAGES; MR BRAIN IMAGE SEGMENTATION; MULTI OBJECTIVE; MULTI-SPECTRAL; MULTIOBJECTIVE CLUSTERING; NUMBER OF CLUSTERS; OPTIMIZATION STRATEGY; PARETO-OPTIMAL FRONT; POINT SYMMETRY; PROTON DENSITY; SEMI-SUPERVISED METHOD; SUB-CLUSTERS; VARIABLE NUMBER;

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; CRYSTAL SYMMETRY; FUZZY CLUSTERING; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; PROBLEM SOLVING; SIMULATED ANNEALING;

MULTIOBJECTIVE OPTIMIZATION;

EID: 79951798951     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10489-010-0231-6     Document Type: Article

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