Learning-based deformable image registration for infant MR images in the first year of life:

Medical Physics

Volumn 44, Issue 1, 2017, Pages 158-170

  Hu, Shunbo ^a,b   Wei, Lifang ^b,c   Gao, Yaozong ^b   Guo, Yanrong ^b   Wu, Guorong ^b   Shen, Dinggang ^b,d  

^a LINYI UNIVERSITY   (China)

^b UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^c FUJIAN AGRICULTURE AND FORESTRY UNIVERSITY   (China)

^d Korea University   (South Korea)

Author keywords

deformable image registration; infant brain MR image; regression forest

Indexed keywords

BRAIN MAPPING; DEFORMATION; FORESTRY; MAGNETIC RESONANCE IMAGING; REGRESSION ANALYSIS;

BRAIN DEVELOPMENT; BRAIN IMAGES; BRAIN MR IMAGES; DEFORMABLE IMAGE REGISTRATION; DEVELOPMENT PHASIS; FIRST YEAR; INFANT BRAIN MR IMAGE; MR-IMAGES; REGISTRATION METHODS; REGRESSION FORESTS;

IMAGE REGISTRATION;

BRAIN DEVELOPMENT; FEMALE; FOREST; HUMAN; HUMAN EXPERIMENT; IMAGE ANALYSIS; INFANT; LEARNING; MALE; REGISTRATION; REMISSION; BRAIN; DIAGNOSTIC IMAGING; GROWTH, DEVELOPMENT AND AGING; IMAGE PROCESSING; MACHINE LEARNING; NEWBORN; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES;

BRAIN; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; INFANT; INFANT, NEWBORN; MACHINE LEARNING; MAGNETIC RESONANCE IMAGING;

EID: 85015605833     PISSN: 00942405     EISSN: 24734209     Source Type: Journal    
DOI: 10.1002/mp.12007     Document Type: Article

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