A spatio-temporal latent atlas for semi-supervised learning of fetal brain segmentations and morphological age estimation

Medical Image Analysis

Volumn 18, Issue 1, 2014, Pages 9-21

  Dittrich, Eva ^a,b   Riklin Raviv, Tammy ^c   Kasprian, Gregor ^a   Donner, René ^a   Brugger, Peter C ^d   Prayer, Daniela ^a   Langs, Georg ^a,e  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

^b PROFACTOR GMBH   (Austria)

^c BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^d Medical University of Vienna   (Austria)

^e MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Fetal brain development; Magnetic resonance imaging; Segmentation; Spatio temporal latent atlas

Indexed keywords

BRAIN DEVELOPMENT; BRAIN SEGMENTATION; CEREBRAL STRUCTURES; CLINICAL APPLICATION; REPRESENTATIVE SAMPLE; SEGMENTATION ACCURACY; SEMI-SUPERVISED LEARNING; SPATIO-TEMPORAL;

BRAIN; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; NEUROIMAGING; POPULATION STATISTICS;

SUPERVISED LEARNING;

AGE DETERMINATION; ARTICLE; BRAIN; BRAIN CORTEX; BRAIN DEVELOPMENT; BRAIN VENTRICLE; CONTROLLED STUDY; FETUS; GESTATION PERIOD; GESTATIONAL AGE; HUMAN; NEUROIMAGING; PRIORITY JOURNAL; SPATIOTEMPORAL ANALYSIS;

FETAL BRAIN DEVELOPMENT; MAGNETIC RESONANCE IMAGING; SEGMENTATION; SPATIO-TEMPORAL LATENT ATLAS;

AGING; ALGORITHMS; ANATOMY, ARTISTIC; ARTIFICIAL INTELLIGENCE; ATLASES AS TOPIC; BRAIN; COMPUTER SIMULATION; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MODELS, ANATOMIC; MODELS, NEUROLOGICAL; PRENATAL DIAGNOSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPATIO-TEMPORAL ANALYSIS; SUBTRACTION TECHNIQUE;

EID: 84884724125     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2013.08.004     Document Type: Article

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