The Neuroimage Analysis Center (NAC) is a National Resource Center in the Biomedical Technology Resource Center (BTRC) program that is developing image analysis algorithms and software tools to improve understanding of brain diseases and to enable innovative treatments. This competitive renewal application focuses on subject-specific analyses of medical imaging data. Underlying NAC's approach is a set of technical expertise and methodologies - Image analysis, applied statistics, tensor processing, time series analysis, and software engineering - that will enable the Center to exploit the atlas-based technologies developed in previous funding cycles to improve the analysis of individual patient data. The proposed work will be performed in four Technical Research and Development (TRD) projects and one Infrastructure project;it will be leveraged by outreach and operations activities, which include training in the use of 3D Slicer, the software platform supported by the Center. The four TRDs encompass microstructure imaging, spatio-temporal disease modeling, anatomical variability modeling, and Slicer engineering. The NAC team of investigators is augmented by subcontractors at GE, UMass Worcester, and Boston University, each of whom will provide unique expertise toward methodological and infrastructure development. The Driving Biomedical Projects (DBPs) will ensure that all Center activities continue to be highly relevant to NIH grantees. These DBPs include research in chronic traumatic encephalopathy, methamphetamine addiction and AIDS, schizophrenia, Alzheimer's disease, Huntington disease, autism, and image guided therapy. The translation of technological research into 3D Slicer as a platform for outreach represents a key deliverable In NAC's role as a resource center. The Center will continue to offer support and training at local and national venues as part of its outreach activities. Close collaboration with clinicians and scientists continues to be critical to the implementation of image analysis tools for the purpose of understanding the brain and treating Its disorders, an Important mission of the NIH.

Public Health Relevance

The Neuroimaging Analysis Center (NAC) Is a National Resource Center in the Biomedical Technology Resource Center (BTRC) program that is developing image analysis algorithms and software tools to improve understanding of brain diseases and to enable Innovative treatments.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Biotechnology Resource Grants (P41)
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Special Emphasis Panel (ZRG1-SBIB-L (40))
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Pai, Vinay Manjunath
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Brigham and Women's Hospital
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Seitz, Johanna; Zuo, Jessica X; Lyall, Amanda E et al. (2016) Tractography Analysis of 5 White Matter Bundles and Their Clinical and Cognitive Correlates in Early-Course Schizophrenia. Schizophr Bull 42:762-71
Zhang, Miaomiao; Golland, Polina (2016) Statistical shape analysis: From landmarks to diffeomorphisms. Med Image Anal 33:155-8
Zhang, Fan; Song, Yang; Cai, Weidong et al. (2016) Dictionary Pruning with Visual Word Significance for Medical Image Retrieval. Neurocomputing 177:75-88
Batmanghelich, Nematollah K; Dalca, Adrian; Quon, Gerald et al. (2016) Probabilistic Modeling of Imaging, Genetics and Diagnosis. IEEE Trans Med Imaging 35:1765-79
Kolesov, Ivan; Lee, Jehoon; Sharp, Gregory et al. (2016) A Stochastic Approach to Diffeomorphic Point Set Registration with Landmark Constraints. IEEE Trans Pattern Anal Mach Intell 38:238-51
Menze, Bjoern H; Van Leemput, Koen; Lashkari, Danial et al. (2016) A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation--With Application to Tumor and Stroke. IEEE Trans Med Imaging 35:933-46
Pujol, Sonia; Baldwin, Michael; Nassiri, Joshua et al. (2016) Using 3D Modeling Techniques to Enhance Teaching of Difficult Anatomical Concepts. Acad Radiol 23:507-16
Li, Mao; Miller, Karol; Joldes, Grand Roman et al. (2016) Biomechanical model for computing deformations for whole-body image registration: A meshless approach. Int J Numer Method Biomed Eng 32:
Margulies, Daniel S; Ghosh, Satrajit S; Goulas, Alexandros et al. (2016) Situating the default-mode network along a principal gradient of macroscale cortical organization. Proc Natl Acad Sci U S A 113:12574-12579
Liu, Sidong; Cai, Weidong; Pujol, Sonia et al. (2016) Cross-View Neuroimage Pattern Analysis in Alzheimer's Disease Staging. Front Aging Neurosci 8:23

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