Biomedical Imaging

Professor

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Developing magnetic resonance imaging (MRI) techniques for assessing the structure, function, and perfusion of the cardiovascular system, particularly in the setting of cardiovascular disease, diabetes, and musculoskeletal disease.

Professor

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Combining advanced methods of targeted drug and gene delivery with biomedical imaging in vivo to explore novel targets and treatment strategies in cardiovascular disease and cancer.

Professor

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Developing ultrasound imaging approaches for cardiovascular disease, including mouse heart imaging, catheter-based imaging and drug delivery, and molecular imaging for diagnosing stroke risk.

Professor

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Developing phage-based nanoparticle techniques for diagnostic imaging, drug target identification, and drug delivery in the setting of pancreatic cancer.

Professor

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Developing magnetic resonance imaging (MRI) techniques for rapid acquisition of image data in the setting of cardiovascular disease and musculoskeletal disease, using tools in physics, signal processing, and image reconstruction.

Professor

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Developing computational predictive models using machine learning and signal and image processing with applications in pathology, radiology, systems biology and mobile sensing.

Assistant Professor

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Working at the nexus of therapeutic ultrasound, advanced imaging, and tumor immunology to design and deploy precision cancer immunotherapy paradigms.

Associate Professor of Radiology and Medical Imaging

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Developing and optimizing quantitative cardiac PET imaging techniquesto address the hypothesis of metabolic remodeling in small animal modelsof myocardial injury and type 2 diabetes.

Associate Professor of Radiology and Medical Imaging

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Developing new pulse-sequence techniques, contrast mechanisms, and hardware for magnetic resonance (MR) imaging of the lung and MR-guided focused ultrasound of the brain.

Professor of Radiology and Medical Imaging

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Development and optimization of magnetic resonance imaging (MRI) techniques with a strong emphasis on theoretical modeling and simulation and on practical implementation and evaluation.

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A multidisciplinary, collaborative, and translational model that is cross-cutting--it applies to multiple diseases, modalities, scales, and areas of expertise.

Bringing UVA MRI Technology to the World

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Through our relationship with Siemens and their research sites, we magnify the usefulness of our research and multiply its applications.

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UVA Brain draws upon talented faculty and students across the University to understanding the brain; seek new treatments for brain diseases and injury; and teach what they have learned.

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The $8 million investment will generate clinical trials and other research that will directly benefit patients.