J
Jagath C. Rajapakse
Researcher at Nanyang Technological University
Publications - 269
Citations - 11256
Jagath C. Rajapakse is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Artificial neural network & Support vector machine. The author has an hindex of 42, co-authored 260 publications receiving 10618 citations. Previous affiliations of Jagath C. Rajapakse include National Institutes of Health & University at Buffalo.
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Journal ArticleDOI
Quantitative Brain Magnetic Resonance Imaging in Attention-Deficit Hyperactivity Disorder
F X Castellanos,Jay N. Giedd,W L Marsh,Susan D. Hamburger,A C Vaituzis,Daniel P. Dickstein,S E Sarfatti,Yolanda C. Vauss,John Snell,Nicholas Lange,Debra Kaysen,Amy L. Krain,G F Ritchie,Jagath C. Rajapakse,Judith L. Rapoport +14 more
TL;DR: This first comprehensive morphometric analysis is consistent with hypothesized dysfunction of right-sided prefrontal-striatal systems in ADHD.
Journal ArticleDOI
Quantitative Magnetic Resonance Imaging of Human Brain Development: Ages 4–18
Jay N. Giedd,John Snell,Nicholas Lange,Jagath C. Rajapakse,B. J. Casey,Patricia Kozuch,A. Catherine Vaituzis,Yolanda C. Vauss,Susan D. Hamburger,Debra Kaysen,Judith L. Rapoport +10 more
TL;DR: Findings highlight gender-specific maturational changes of the developing brain and the need for large gender-matched samples in pediatric neuropsychiatric studies.
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Quantitative MRI of the temporal lobe, amygdala, and hippocampus in normal human development: Ages 4–18 years
Jay N. Giedd,A. Catherine Vaituzis,Susan D. Hamburger,Nicholas Lange,Jagath C. Rajapakse,Debra Kaysen,Yolanda C. Vauss,Judith L. Rapoport +7 more
TL;DR: The volume of the temporal lobe, superior temporal gyrus, amygdala, and hippocampus was quantified from magnetic images of the brains of 99 healthy children and adolescents aged 4–18 years, consistent with previous preclinical and human studies that have indicated hormonal responsivity and extend quantitative morphologic findings from the adult literature.
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Statistical approach to segmentation of single-channel cerebral MR images
TL;DR: The proposed scheme for segmentation is based on the iterative conditional modes (ICM) algorithm in which measurement model parameters are estimated using local information at each site, and the prior model parametersare estimated using the segmentation after each cycle of iterations.
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Sexual dimorphism of the developing human brain
Jay N. Giedd,Francisco Xavier Castellanos,Jagath C. Rajapakse,A C Vaituzis,Judith L. Rapoport +4 more
TL;DR: Sex differences in brain structures during this developmental period between 4 and 18 years of age may be related to the observed sex differences in age of onset, prevalence, and symptomatology seen in nearly all neuropsychiatric disorders of childhood.