Combining morphological information in a manifold learning framework: application to neonatal MRI.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

Volumn 13, Issue Pt 3, 2010, Pages 1-8

  Aljabar, P ^a   Wolz, R ^b   Srinivasan, L ^b   Counsell, S ^b   Boardman, J P ^b   Murgasova, M ^b   Doria, V ^b   Rutherford, M A ^b   Edwards, A D ^b   Hajnal, J V ^b   Rueckert, D ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; GROWTH, DEVELOPMENT AND AGING; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NEWBORN; NUCLEAR MAGNETIC RESONANCE IMAGING; PRENATAL DIAGNOSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFANT, NEWBORN; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; PRENATAL DIAGNOSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 80053536591     PISSN: None     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (0)