Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

P Aljabar

Showing results (11-20 of 15) with videos related to

Pageof 2
Sort By:
You have reached the last page of results.This site can display upto 15 results.
Neuroimage|September 6, 2015
Machine-learning to characterise neonatal functional connectivity in the preterm brainG Ball, P Aljabar, T Arichi, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 1, 2010
Combining morphological information in a manifold learning framework: application to neonatal MRIP Aljabar, R Wolz, L Srinivasan, et al.
Neuroimage|October 9, 2007
Assessment of brain growth in early childhood using deformation-based morphometryP Aljabar, K K Bhatia, M Murgasova, et al.
Cerebral Cortex (New York, N.Y. : 1991)|April 3, 2013
Whole-brain mapping of structural connectivity in infants reveals altered connection strength associated with growth and preterm birthA S Pandit, E Robinson, P Aljabar, et al.
Neuroimage|May 11, 2010
A common neonatal image phenotype predicts adverse neurodevelopmental outcome in children born pretermJ P Boardman, C Craven, S Valappil, et al.
Pageof 2

Showing results (11-20 of 15) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 15 results.
Neuroimage|September 6, 2015
Machine-learning to characterise neonatal functional connectivity in the preterm brainG Ball, P Aljabar, T Arichi, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 1, 2010
Combining morphological information in a manifold learning framework: application to neonatal MRIP Aljabar, R Wolz, L Srinivasan, et al.
Neuroimage|October 9, 2007
Assessment of brain growth in early childhood using deformation-based morphometryP Aljabar, K K Bhatia, M Murgasova, et al.
Cerebral Cortex (New York, N.Y. : 1991)|April 3, 2013
Whole-brain mapping of structural connectivity in infants reveals altered connection strength associated with growth and preterm birthA S Pandit, E Robinson, P Aljabar, et al.
Neuroimage|May 11, 2010
A common neonatal image phenotype predicts adverse neurodevelopmental outcome in children born pretermJ P Boardman, C Craven, S Valappil, et al.
Pageof 2