Radiology

Brain imaging in aging, Alzheimer's disease, and related diseases (ADRD) with specific focus of translation of novel PET tracers and MR sequences into human studies, clinical trials, and clinical patient populations.

Research keywords: Alzheimer; MRI; PET

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The Personomics Lab, led by Janine Bijsterbosch, PhD, aims to understand how brain connectivity patterns differ from one person to the next by studying the personalized connectome. Using population datasets such as the UK Biobank, the Personomics Lab adopts cutting edge computational techniques to improve the interpretability and reliability of resting state functional connectivity networks and investigate multimodal brain correlates of mental health disorders such as depression.

Research keywords: neuroimaging; mental health; computational neuroscience

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The Chaney lab focuses on the development and evaluation of novel imaging biomarkers to investigate the inflammatory component of neurodegenerative diseases. The goals of this work are to enhance understanding, detection, and treatment of devastating neurological diseases through the development of non-invasive translational molecular imaging strategies. Specifically, we are interested in developing Positron Emission Tomography (PET) tracers targeting the innate immune system and defining the role of peripheral and central nervous system (CNS) immune responses in neurodegeneration (e.g., Alzheimer’s disease and multiple sclerosis) and infection. To achieve this, we employ multidisciplinary research at the interface of neuroscience, radiology, and immunology.

Research keywords: Molecular imaging; Neuroinflammation; Neurodegeneratoin

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Our diverse and interdisciplinary Brain Light Laboratory develops and applies optical methods called high-density diffuse optical tomography for assessing human brain health and function. We develop next generation advancements in hardware and algorithms to obtain higher reliability and image quality. We are currently focused on applications in childhood development, including measuring brain function concurrently with natural behavior in autistic and neurotypical children, as well as point-of-care bedside assessment of brain health in acute care settings in children with congenital heart disease. We also develop and disseminate computational tools for modeling, processing, and analyses of optical data.

Research keywords: optical; neuroscience; human

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The Gastounioti Lab, also known as the Breast Image Computing Lab, conducts translational breast imaging research towards prediction, early diagnosis, prognosis and response to treatment for breast cancer. Our vision is to foster a vibrant and intellectually stimulating research environment by combining elements of computational breast image analysis, artificial intelligence, and informatics to build technologies with a potential for clinical impact in advancing breast cancer screening and prevention strategies.

Research keywords: computational imaging; artificial intelligence; breast cancer screening

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Abhinav K. Jha's research is in the design, evaluation and translation of computational medical imaging methods for optimized performance in diagnostic and therapeutic tasks using quantitative measures of task performance. For this purpose, his group develops novel physics and artificial intelligence (AI)-based methods for image reconstruction, image enhancement, image analysis and task-based image-quality evaluation. One major research direction is in integrating AI and task-based assessment to make medical imaging more comfortable and accessible for patients by reducing acquisition dose and scanning times, and more valuable for physicians by automating image-analysis procedures and providing imaging biomarkers to monitor disease response. This research direction also includes studying the clinical deployment and ethical aspects of AI algorithms. Another major direction of research is developing low-count quantitative imaging methods for personalizing emerging cancer treatments. Towards this goal, his group develops statistical signal-processing approaches that maximize the extracted task-specific information from data measured by imaging systems.

Research keywords: Computational medical imaging; Artificial intelligence; Imaging Science

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Our lab uses biomolecules to deliver imaging or cytotoxic cargo, multimodal imaging to monitor the binding of molecular-targeted compounds, acute and temporal pharmacologic approaches to modulate tumor biology, and basic tumor biology combined with preclinical knowledge to improve cancer diagnosis and treatment.

Research keywords: Cancer; Antibody; Imaging

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TIRs is reaching out to prospective graduate students in Chemistry, Biochemistry and Neurosciences. This T32 training program provides a unique opportunity for recently graduated students interested in transitioning their careers into applied molecular imaging focused on design, preclinical validation, development, and translation of PET molecular imaging agents for diagnostic clinical nuclear medicine for application in neurodegenerative diseases (ADRDs).

Research keywords: PET; Probe-Development; Translational-Imaging

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My work is at the intersection of medical image analysis, machine learning, and computational neuroscience. I focus on developing novel computational methods to extract information from imaging data and delineate patterns in large heterogeneous data sets, towards improving patient-specific diagnosis and advancing our understanding of brain structure and function in health and disease. Current applications include aging and Alzheimer's Disease, as well as development and neuropsychiatric disorders

Research keywords: Machine Learning; Medical Image Analysis; Neuroimaging

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Please see my links.
https://profiles.wustl.edu/en/persons/jinbin-xu

Research keywords: Cancer; Parkinson disease; Alzheimer Disease

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