- OVERALL The LONIR is focused on developing innovative solutions for the investigation of imaging, genetics, behavioral and clinical data. The LONIR structure is designed to facilitate studies of dynamically changing anatomic frameworks, e.g., developmental, neurodegenerative, traumatic, and metastatic, by providing methods for the comprehensive understanding of the nature and extent of these processes. Specifically, TR&D1 (Data Science) focuses on methodological developments for the management and informatics of brain and related data. This project will develop and issue new methods for robust scientific data management to create an environment where scientific analyses can be reproduced and/or enhanced, data can be easily discovered and reused, and analysis results can be visualized and made publicly searchable. TR&D2 (Diffusion MRI and Connectomics) seeks to advance the study of brain connectivity using diffusion imaging and its powerful extensions. This project will go beyond traditional tensor models of diffusion for assessing tissue and fiber microstructure and connectivity, develop tract-based statistical analysis tools using Deep Learning, introduce novel adaptive connectivity mapping approaches, using L1 fusion of multiple tractography methods, and provide mechanisms to study connectivity and diffusion imaging over 10,000 subjects. (This technology and these methods will be managed and executed by the TR&D1 framework to distributed datasets totaling over 10,000 subjects). Lastly, our TR&D3 (Intrinsic Surface Mapping) develops a general framework for surface mapping in the high dimensional Laplace-Beltrami embedding space via the mathematical optimization of their Riemannian metric. Our approach here overcomes fundamental limitations in existing methods based on spherical registration by eliminating the metric distortion during the parameterization step, thus achieving much improved accuracy in mapping brain anatomy. Coupled with a mature and efficient administrative structure and comprehensive training and dissemination, this program serves a wide and important need in the scientific community.
- OVERALL The comprehensive suite of technologies include algorithmic and computational methods for image management, processing, data analysis and visualization. The technologies are ideally suited to enable holistic studies of the interactions between different imaging data modalities, phenotypic population characteristics, and physiological brain connectivity.
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