A probabilistic, non-parametric framework for inter-modality label fusion

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

Volumn 8151 LNCS, Issue PART 3, 2013, Pages 576-583

  Iglesias, Juan Eugenio ^a   Sabuncu, Mert Rory ^a   Van Leemput, Koen ^a,b,c  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^c AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN FRAMEWORKS; CONDITIONAL DISTRIBUTION; EXPECTATION - MAXIMIZATIONS; GENERATIVE MODEL; INTER MODALITIES; NON-PARAMETRIC; PROTON DENSITY; VOXEL INTENSITIES;

ALGORITHMS; CHANNEL ESTIMATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGE PROCESSING; MAXIMUM PRINCIPLE; MEDICAL COMPUTING;

IMAGE SEGMENTATION;

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

ALGORITHMS; BRAIN; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, ANATOMIC; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84894632325     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40760-4_72     Document Type: Conference Paper

References (11)

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