GRAM: A framework for geodesic registration on anatomical manifolds

Medical Image Analysis

Volumn 14, Issue 5, 2010, Pages 633-642

  Hamm, Jihun ^a   Ye, Dong Hye ^b   Verma, Ragini ^a,b   Davatzikos, Christos ^a,b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Diffeomorphism; Geodesic registration; Large deformation; Manifold learning

Indexed keywords

ANATOMICAL VARIATIONS; BRAIN IMAGES; DIFFEOMORPHISMS; GEODESIC PATHS; LARGE DEFORMATIONS; MANIFOLD LEARNING; MEDICAL IMAGE REGISTRATION; REAL DATABASE; REGISTRATION METHODS; REGISTRATION PROBLEMS; SHORTEST PATH;

GEODESY; GRAPH THEORY; IMAGE REGISTRATION; LEARNING ALGORITHMS; MEDICAL IMAGING;

DEFORMATION;

ADULT; AGED; ANATOMICAL VARIATION; ARTICLE; CONTROLLED STUDY; DATA BASE; EMPIRICISM; GEODESIC REGISTRATION ON ANATOMICAL MANIFOLDS; HUMAN; IMAGE ANALYSIS; LEARNING; MAJOR CLINICAL STUDY; MOUSE; NEUROIMAGING; NONHUMAN; PRIORITY JOURNAL; REGISTRATION; SELF-DIRECTED LEARNING; SIMULATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 77954581711     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2010.06.001     Document Type: Article

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