A general fast registration framework by learning deformation-appearance correlation

IEEE Transactions on Image Processing

Volumn 21, Issue 4, 2012, Pages 1823-1833

  Kim, Minjeong ^a   Wu, Guorong ^a   Yap, Pew Thian ^a   Shen, Dinggang ^a  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

Deformation prediction; fast image registration; principal component analysis (PCA); support vector regression (SVR)

Indexed keywords

ACCURACY IMPROVEMENT; COMPUTATION TIME; DEFORMATION FIELD; DEFORMATION PREDICTION; FAST IMAGE REGISTRATION; IMAGE APPEARANCE; LOCAL MINIMUMS; MEDICAL IMAGES; PERFORMANCE IMPROVEMENTS; PRINCIPAL COMPONENT ANALYSIS (PCA); REGISTRATION ALGORITHMS; RESIDUAL DEFORMATION; STATISTICAL CORRELATION; SUBJECT-SPECIFIC; SUBOPTIMAL SOLUTION; SUPPORT VECTOR REGRESSION (SVR); TEMPLATE IMAGES;

ALGORITHMS; FORECASTING; PRINCIPAL COMPONENT ANALYSIS;

DEFORMATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

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

EID: 84859010761     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2011.2170698     Document Type: Article

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