Particle-based shape analysis of multi-object complexes

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

Volumn 5241 LNCS, Issue PART 1, 2008, Pages 477-485

  Cates, Joshua ^a   Fletcher, P Thomas ^a   Styner, Martin ^b   Hazlett, Heather Cody ^b   Whitaker, Ross ^a  

^a UNIVERSITY OF UTAH   (United States)

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

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN STRUCTURE; CLINICAL STUDY; CORRESPONDENCE PROBLEMS; HYPOTHESIS TESTING; MODELING AND ANALYSIS; MULTIOBJECT; NON-PARAMETRIC; OBJECT POSE; OBJECT SURFACE; PARTICLE SYSTEMS; PCA MODE; SHAPE ANALYSIS; SHAPE MODELING; SHAPE SPACE; SIMULATION-BASED; STATISTICAL ANALYSIS; SURFACE POINTS;

COMPUTER SCIENCE; MEDICAL IMAGING;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTISM; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; AUTISTIC DISORDER; BRAIN; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 79551690120     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_57     Document Type: Conference Paper

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