Unsupervised Learning of an Atlas from Unlabeled Point-Sets

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 26, Issue 2, 2004, Pages 160-172

  Chui, Haili ^a   Rangarajan, Anand ^b   Zhang, Jie ^b   Leonard, Christiana Morison ^c  

^a R2 Technology   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

^c UNIVERSITY OF FLORIDA COLLEGE OF MEDICINE   (United States)

Author keywords

Atlases; Clustering; Correspondence; Deformation; Deterministic annealing; EM algorithm; Mixture models; Nonrigid; Point sets; Shapes; Thin plate splines; Unsupervised learning

Indexed keywords

ATLASES; CORRESPONDENCE; DETERMINISTIC ANNEALING; EM ALGORITHM; NONGRID; POINT-SETS; SHAPES; THIN-PLATE SPLINES; UNSUPERVISED LEARNING;

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL METHODS; COMPUTER VISION; EIGENVALUES AND EIGENFUNCTIONS; LEARNING SYSTEMS; MATRIX ALGEBRA; PROBABILITY DENSITY FUNCTION; PROBLEM SOLVING; STATISTICAL METHODS;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BOOK; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; CORPUS CALLOSUM; EVALUATION; HIPPOCAMPUS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; ATLASES; CLUSTER ANALYSIS; COMPUTER GRAPHICS; CORPUS CALLOSUM; HIPPOCAMPUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE; USER-COMPUTER INTERFACE;

EID: 0742303470     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2004.1262178     Document Type: Article

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