Two fully-unsupervised methods for MR brain image segmentation using SOM-based strategies

Applied Soft Computing Journal

Volumn 13, Issue 5, 2013, Pages 2668-2682

  Ortiz, A ^a   Gorriz J M ^b   Ramirez J ^b   Salas Gonzalez D ^b   Llamas Elvira, J M ^c  

^a UNIVERSITY OF MÁLAGA   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

^c HOSPITAL UNIVERSITARIO VIRGEN DE LAS NIEVES   (Spain)

Author keywords

Feature extraction; Genetic algorithms; Image segmentation; MRI; Neural networks; Self organizing maps

Indexed keywords

BRAIN MAPPING; CLUSTERING ALGORITHMS; CONFORMAL MAPPING; EXTRACTION; FEATURE EXTRACTION; GENETIC ALGORITHMS; IMAGE PROCESSING; MAGNETIC RESONANCE IMAGING; NEURAL NETWORKS; NEURODEGENERATIVE DISEASES; NUCLEAR MEDICINE; SELF ORGANIZING MAPS; TISSUE;

ALZHEIMER'S DISEASE; EVOLUTIONARY COMPUTING; HIGH RESOLUTION IMAGE; MR BRAIN IMAGE SEGMENTATION; SECOND-ORDER FEATURES; SEGMENTATION RESULTS; UNSUPERVISED APPROACHES; VOXEL CLASSIFICATIONS;

IMAGE SEGMENTATION;

EID: 84885578159     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2012.11.020     Document Type: Article

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