Adaptive neonate brain segmentation

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

Volumn 6893 LNCS, Issue PART 3, 2011, Pages 378-386

  Cardoso, M Jorge ^a   Melbourne, Andrew ^a   Kendall, Giles S ^a   Modat, Marc ^a   Hagmann, Cornelia F ^a   Robertson, Nicola J ^a   Marlow, Neil ^a   Ourselin, Sebastien ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE TECHNIQUE; ANATOMICAL VARIABILITY; BIRTHWEIGHT; BRAIN MRI; BRAIN SEGMENTATION; BRAIN VOLUME; EM ALGORITHMS; EXPECTATION-MAXIMISATION; GESTATIONAL AGE; INHOMOGENEITY CORRECTION; MARKOV RANDOM FIELDS; MAXIMUM A POSTERIORI; MULTI-MODEL; PARTIAL VOLUME EFFECT; PARTIAL VOLUMES; SEGMENTATION ALGORITHMS; SPATIAL HOMOGENEITY;

ALGORITHMS; MAXIMUM LIKELIHOOD; MEDICAL COMPUTING; PEDIATRICS; TISSUE;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; BRAIN MAPPING; CEREBROSPINAL FLUID; GROWTH, DEVELOPMENT AND AGING; HUMAN; IMAGE PROCESSING; METHODOLOGY; NEWBORN; NORMAL DISTRIBUTION; PATHOLOGY; PREMATURITY; PROBABILITY; REPRODUCIBILITY; STATISTICAL MODEL;

ALGORITHMS; BRAIN; BRAIN MAPPING; CEREBROSPINAL FLUID; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; INFANT, NEWBORN; INFANT, PREMATURE; LIKELIHOOD FUNCTIONS; MARKOV CHAINS; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS;

EID: 82255183303     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23626-6_47     Document Type: Conference Paper

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