Efficacy of texture, shape, and intensity feature fusion for posterior-fossa tumor segmentation in MRI

IEEE Transactions on Information Technology in Biomedicine

Volumn 15, Issue 2, 2011, Pages 206-213

  Ahmed, Shaheen ^a   Iftekharuddin, Khan M ^a,b   Vossough, Arastoo ^c  

^a University of Memphis   (United States)

^b UNIVERSITY OF TENNESSEE HEALTH SCIENCE CENTER   (United States)

^c CHILDREN S HOSPITAL OF PHILADELPHIA   (United States)

Author keywords

Expectation maximization (EM); fractal dimension (FD); KullbackLeibler divergence (KLD); MRI modalities; multi fractional Brownian motion (mBm)

Indexed keywords

BRAIN MRI; BRAIN TUMORS; EXPECTATION MAXIMIZATION; EXPECTATION-MAXIMIZATION ALGORITHMS; FEATURE FUSION; FEATURE RANKING; FEATURE SELECTION; FRACTIONAL BROWNIAN MOTION; IMAGE FEATURES; INVERSION RECOVERY; KULLBACK-LEIBLER DIVERGENCE; LEVEL SETS; MRI MODALITIES; MULTI-MODAL; MULTI-MODALITY; MULTIFRACTIONAL BROWNIAN MOTION; NORMAL TISSUE; PATIENT DATA; PEDIATRIC PATIENTS; SEGMENTATION TECHNIQUES; SIMILARITY METRICS; TEXTURE FEATURES; TUMOR SEGMENTATION;

ALGORITHMS; BROWNIAN MOVEMENT; FINITE DIFFERENCE METHOD; FRACTAL DIMENSION; HOSPITAL DATA PROCESSING; IMAGE SEGMENTATION; MAXIMUM PRINCIPLE; OPTIMIZATION; PARTIAL DISCHARGES; PEDIATRICS; TEXTURES; TUMORS;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; BRAIN; CEREBELLUM TUMOR; CHILD; FRACTAL ANALYSIS; HUMAN; IMAGE PROCESSING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PRINCIPAL COMPONENT ANALYSIS;

ALGORITHMS; BRAIN; CHILD; FRACTALS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; INFRATENTORIAL NEOPLASMS; MAGNETIC RESONANCE IMAGING; PRINCIPAL COMPONENT ANALYSIS;

EID: 79952476875     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2011.2104376     Document Type: Article

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