Optimal data-driven sparse parameterization of diffeomorphisms for population analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6801 LNCS, Issue , 2011, Pages 123-134

  Durrleman, Sandy ^a   Prastawa, Marcel ^a   Gerig, Guido ^a   Joshi, Sarang ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DEFORMATION; GEOMETRY; MEDICAL COMPUTING; MEDICAL IMAGING; OPTIMIZATION; POPULATION STATISTICS;

ANATOMICAL IMAGES; ANATOMICAL VARIATIONS; ATLAS CONSTRUCTION; CONTROL POINT; DATA DRIVEN; DIFFEOMORPHISMS; GEOMETRIC DESCRIPTOR; OPTIMAL DATA; POPULATION ANALYSIS; TEMPLATE IMAGES;

PARAMETERIZATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUDIOVISUAL EQUIPMENT; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ANATOMY AND HISTOLOGY; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MAGNETIC RESONANCE IMAGING; METHODS; MODELS, ANATOMIC; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

IM; MLCS; MLOWN; NLM;

EID: 79959626160     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22092-0_11     Document Type: Conference Paper

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