A hybrid geometricstatistical deformable model for automated 3-d segmentation in brain MRI

IEEE Transactions on Biomedical Engineering

Volumn 56, Issue 7, 2009, Pages 1838-1848

  Huang, Albert ^a   Abugharbieh, Rafeef ^a   Tam, Roger ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

3 D image segmentation; Brain segmentation; Deformable models; Geodesic active contour

Indexed keywords

3-D IMAGE SEGMENTATION; 3D SEGMENTATION; ACCURACY LEVEL; ANATOMICAL STRUCTURES; AUTOMATED TISSUES; BRAIN MRI; BRAIN SEGMENTATION; DEFORMABLE MODELS; EDGE-BASED; GEODESIC ACTIVE CONTOUR; GRAY MATTER; IMAGE EDGE; LEVEL SETS; REGION-BASED; SEGMENTATION RESULTS; STATISTICAL HOMOGENEITY; WHITE MATTER;

BRAIN MODELS; DEFORMATION; DIGITAL IMAGE STORAGE; FEATURE EXTRACTION; GEODESY; IMAGE SEGMENTATION;

THREE DIMENSIONAL;

ACCURACY; ANALYTIC METHOD; ARTICLE; BRAIN REGION; BRAIN SCINTISCANNING; CONTROLLED STUDY; DIFFUSION WEIGHTED IMAGING; GEOMETRY; HYBRID GEOMETRIC STATISTICAL DEFORMABLE MODEL; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; THREE DIMENSIONAL IMAGING; VALIDATION PROCESS; ALGORITHM; BRAIN; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; METHODOLOGY; REPRODUCIBILITY; STATISTICAL MODEL;

ALGORITHMS; BRAIN; COMPUTER SIMULATION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; PHANTOMS, IMAGING; REPRODUCIBILITY OF RESULTS;

EID: 67650927371     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2009.2017509     Document Type: Article

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