The National Institute of Neurological Disorders and Stroke (NINDS) awarded a $621,617 Project Grant (CFDA 93.853) to the University of North Carolina at Chapel Hill to develop and optimize a rapid, high-resolution quantitative magnetic resonance imaging (MRI) technique for brain imaging. The project aims to leverage expertise in MRI, machine learning, and pulse sequence optimization to create a new B1-insensitive MRI fingerprinting method with improved accuracy and precision in tissue quantification. Key objectives include developing 3D high-resolution brain imaging capabilities, incorporating motion robustness through novel fat navigators, and leveraging deep learning to accelerate both data acquisition and post-processing. The project will also create a cloud-based MRI post-processing pipeline to simplify clinical translation and validation of the proposed methods for patients with neurological diseases. The award period runs from September 2024 through June 2029.
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