Improved inference in Bayesian segmentation using Monte Carlo sampling: Application to hippocampal subfield volumetry

Medical Image Analysis

Volumn 17, Issue 7, 2013, Pages 766-778

  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

Bayesian modeling; Hippocampal subfields; Monte Carlo sampling; Segmentation

Indexed keywords

BAYESIAN MODELING; BAYESIAN SEGMENTATION; COMPUTATIONALLY EFFICIENT; INDIVIDUAL STRUCTURES; MARKOV CHAIN MONTE CARLO TECHNIQUES; MONTE CARLO SAMPLING; SEGMENTATION ALGORITHMS; SUBFIELDS;

BAYESIAN NETWORKS; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MONTE CARLO METHODS;

UNCERTAINTY ANALYSIS;

AGED; ALZHEIMER DISEASE; ARTICLE; BAYES THEOREM; BRAIN SIZE; CONTROLLED STUDY; DISEASE CLASSIFICATION; FEMALE; HIPPOCAMPUS; HUMAN; MAJOR CLINICAL STUDY; MALE; MONTE CARLO METHOD; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; PROBABILITY; VOLUMETRY;

BAYESIAN MODELING; HIPPOCAMPAL SUBFIELDS; MONTE CARLO SAMPLING; SEGMENTATION;

ALGORITHMS; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; DATA INTERPRETATION, STATISTICAL; HIPPOCAMPUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MONTE CARLO METHOD; ORGAN SIZE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY;

EID: 84879887285     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2013.04.005     Document Type: Article

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