Our research focuses on developing and translating computational neuroimaging methods to delineate human brain structure-function relationships. Current applications include identifying biomarkers of disease progression and treatment response in multiple sclerosis and other neurodegenerative diseases.
The Molecular Imaging and Precision Medicine Lab has four Technology Research and Development (TR&D) projects that provide a platform on which new technology is developed and disseminated. The TR&Ds are complementary and integrated and extend from the development of reagents to detect and promote an immune reactive tumor microenvironment to the synthesis of nanodrones to treat cancer and combined small-molecule diagnostic and therapeutics (theranostic agents). We focus on generation of next-generation precision platforms, tools and techniques for tackling problems at the forefront of biomedical research with a focus on those that will lead to near-term translation.
In our lab, we focus on the mechanisms of cerebrovascular reactivity, exploring how blood vessels in the brain respond to changes in carbon dioxide, blood pressure, and other stimuli.
The Henning lab develops novel ultra-high field MRI and metabolic MRI methodology for human application and translates it to neuroscientific, physiological and clinical trials in brain, spine, heart and muscle disorders.
SPIL is dedicated to advancing patient care through the development and validation of cutting-edge radionuclide imaging technologies for single photon emission computed tomography (SPECT) and positron emission tomography (PET). By harnessing the power of deep learning, we aim to address key limitations of PET and SPECT imaging—such as low spatial resolution and slow data acquisition—to significantly enhance diagnostic capabilities.
The Davenport Lab is a branch of the ANSIR Lab at UTSW that focuses on quantitative methods for human brain imaging, primarily using MRI and Magnetoencephalography (MEG).
The Liu Lab is Interested in developing and evaluating novel therapies, notably targeting tumor vasculatures.
We develop the theory and application of deep learning to improve diagnoses, prognoses and therapy decision making.
The research focus in the Corbin lab investigates strategies that exploits the deviant metabolism of cancer cells (namely the reprogramming of lipid metabolism and altered redox biology) for therapeutic purposes.
The main focus of the Vinogradov Lab is developing MRI methods that are based on the intrinsic biochemical processes and physical properties of the tissue: chemical exchange rearrangements, molecular networks, and relaxation.
