The primary objective of the Neuroimaging Core is to serve the clinical Projects 1 and 2 which utilize MRIimage acquisition and processing technology.. The core provides quantitative measurements of structuralMRI (sMRI), MR Diffusion Tensor Imaging (DTI), and functional MRI (fMRI), and prepares the quantitativeresults for analysis by the Biostatistics Core. The core utilizes images from state-of-the-art high-fieldscanner MRI technology, and ensures optimized pulse sequences for imaging of neonates and youngchildren (3T Siemens Allegra head-only) and adolescents. (3T GE). The core will provide well establishedand validated image analysis methods and will also introduce novel methods driven by the needs of theseprojects. Given the specialized expertise of our multi-disciplinary group and the close collaboration of ourresearchers with other large national programs which are of crucial importance for this project(Bioinformatics Research Network BIRN, National Alliance of Medical Image Computing NA-MIC, NLM-sponsored Insight Toolkit ITK developments), we will not only provide service to projects with well-established methodology, but will continue to develop advanced, novel image processing tools necessary toadvance the field. This Core enables Center investigators to utilize optimal methods for image data analysisusing the full range of MRI capabilities, and thus enables imaging research which addresses highly relevantpre-clinical research of brain development and alterations thereof in subjects at risk for schizophrenia.Focusing on the earliest age range possible for neuroimaging (neonates to 6 year old subjects) with studyingbrain growth in a longitudinal study (which provides a perspective that is unattainable with cross-sectionalsamples), and secondly focusing on altered brain structure and function in children and adolescence atgenetric risk for schizophrenia, coupled with applying novel innovative image analysis tools, are all inaccordance with the mission of NIH funded projects to get better insight into cause and origin of disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Specialized Center (P50)
Project #
2P50MH064065-06
Application #
7333022
Study Section
Special Emphasis Panel (ZMH1-ERB-S (03))
Project Start
2007-08-01
Project End
2012-07-31
Budget Start
2007-08-09
Budget End
2008-07-31
Support Year
6
Fiscal Year
2007
Total Cost
$278,443
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Type
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Lyu, Ilwoo; Kim, Sun Hyung; Girault, Jessica B et al. (2018) A cortical shape-adaptive approach to local gyrification index. Med Image Anal 48:244-258
Stephens, Rebecca L; Langworthy, Benjamin; Short, Sarah J et al. (2018) Verbal and nonverbal predictors of executive function in early childhood. J Cogn Dev 19:182-200
Girault, Jessica B; Langworthy, Benjamin W; Goldman, Barbara D et al. (2018) The Predictive Value of Developmental Assessments at 1 and 2 for Intelligence Quotients at 6. Intelligence 68:58-65
Tu, Liyun; Styner, Martin; Vicory, Jared et al. (2018) Skeletal Shape Correspondence Through Entropy. IEEE Trans Med Imaging 37:1-11
Jha, Shaili C; Xia, Kai; Schmitt, James Eric et al. (2018) Genetic influences on neonatal cortical thickness and surface area. Hum Brain Mapp 39:4998-5013
Chen, Haiwei; Budin, Francois; Noel, Jean et al. (2017) White Matter Fiber-based Analysis of T1w/T2w Ratio Map. Proc SPIE Int Soc Opt Eng 10133:
Lee, Seung Jae; Steiner, Rachel J; Yu, Yang et al. (2017) Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y. Proc Natl Acad Sci U S A 114:148-153
Wang, Yan; Ma, Guangkai; An, Le et al. (2017) Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI. IEEE Trans Biomed Eng 64:569-579
Xia, K; Zhang, J; Ahn, M et al. (2017) Genome-wide association analysis identifies common variants influencing infant brain volumes. Transl Psychiatry 7:e1188
Sadeghi, Neda; Gilmore, John H; Gerig, Guido (2017) Twin-singleton developmental study of brain white matter anatomy. Hum Brain Mapp 38:1009-1024

Showing the most recent 10 out of 187 publications