Hybrid artificial neural network segmentation of precise and accurate inversion recovery (PAIR) images from normal human brain

Magnetic Resonance Imaging

Volumn 18, Issue 10, 2000, Pages 1245-1253

  Glass, John O ^a   Reddick, Wilburn E ^a,b   Goloubeva, Olga ^a   Yo, Virginia ^a,c   Steen, R Grant ^a,d  

^a ST JUDE CHILDREN S RESEARCH HOSPITAL   (United States)

^b UNIVERSITY OF MEMPHIS   (United States)

^c HOWARD UNIVERSITY COLLEGE OF MEDICINE   (United States)

^d UNIVERSITY OF TENNESSEE COLLEGE OF MEDICINE   (United States)

Author keywords

Image segmentation and classification; Neural network; Quantitative T1 analysis

Indexed keywords

ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; BRAIN; CEREBROSPINAL FLUID; DIAGNOSTIC ACCURACY; FEMALE; GRAY MATTER; HUMAN; HUMAN EXPERIMENT; IMAGE ANALYSIS; MALE; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE DIAGNOSIS; WHITE MATTER;

ADOLESCENT; ADULT; ALGORITHMS; BRAIN; CHI-SQUARE DISTRIBUTION; CHILD; CHILD, PRESCHOOL; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER);

EID: 0034491662     PISSN: 0730725X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0730-725X(00)00218-6     Document Type: Article

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