Skull segmentation in 3D neonatal MRI using hybrid Hopfield Neural Network

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Volumn , Issue , 2010, Pages 4060-4063

  Daliri, M ^a,b   Abrishami Moghaddam, H ^a,b   Ghadimi, S ^a,b   Momeni, M ^a,b   Harirchi, F ^a,b   Giti, M ^c  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

^b UNIVERSITÉ DE PICARDIE JULES VERNE   (France)

^c TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

Bayesian clustering; Component; Hybrid Hopfield Neural Network; Morphological model; Region of Interest (ROI); Skull segmentation

Indexed keywords

BAYESIAN CLUSTERING; COMPONENT; HYBRID HOPFIELD NEURAL NETWORK; MORPHOLOGICAL MODEL; REGION OF INTEREST; SKULL SEGMENTATION;

BAYESIAN NETWORKS; HOPFIELD NEURAL NETWORKS; IMAGE SEGMENTATION; MAGNETIC RESONANCE; PEDIATRICS;

NEURAL NETWORKS;

ARTICLE; AUDIOVISUAL EQUIPMENT; BAYES THEOREM; ELECTROENCEPHALOGRAPHY; HISTOLOGY; HUMAN; METHODOLOGY; NEWBORN; NUCLEAR MAGNETIC RESONANCE IMAGING; PROBABILITY; SKULL;

BAYES THEOREM; ELECTROENCEPHALOGRAPHY; HUMANS; INFANT, NEWBORN; MAGNETIC RESONANCE IMAGING; MODELS, ANATOMIC; PROBABILITY; SKULL;

EID: 78650820375     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2010.5627619     Document Type: Conference Paper

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