Session Chairs:
Jhimli Mitra, GE Healthcare (United States); Christian Boehm, ETH Zurich (Switzerland)
8:30 AM - 8:35 AM:
Welcome and introduction
8:35 AM - 8:40 AM:
Award announcements
- Robert F. Wagner Award finalists for conferences 13406 and 13412
- Image Processing Student Paper Award, sponsored by:
8:40 AM - 9:20 AM:
Integrating computational approaches to unravel alzheimer's disease and co-pathologies: a biomarker-driven approach to precision medicine
Duygu Tosun-Turgut, Medical Imaging Informatics and Artificial Intelligence, Univ. of California, San Francisco (United States)
Early detection and intervention in neurodegenerative diseases hold the potential to significantly impact patient outcomes. This presentation will explore the development of multi-disciplinary and multi-modality biomarkers to identify individuals at risk and monitor disease progression. By combining advanced imaging techniques, such as MRI, and PET, with fluid biomarkers, we aim to detect subtle changes in brain structure and function that precede clinical symptoms. These biomarkers could serve as powerful tools for early diagnosis, enabling timely intervention and potentially delaying disease onset. Furthermore, by identifying individuals at highest risk, we can optimize the design of clinical trials and accelerate the development of effective therapies. Ultimately, our goal is to improve the lives of individuals with neurodegenerative diseases through early detection, precise diagnosis, and targeted treatment.
Duygu Tosun-Turgut is a Professor of Radiology and Biomedical Imaging at University of California San Francisco and the Founding Director of Medical Imaging Informatics and Artificial Intelligence at the San Francisco Veterans Affairs Medical Center. Her research focuses on neuroimaging, neurodegenerative diseases, and psychiatric disorders. The goal of her research is to develop multi-modal biomarkers using advanced imaging technology that can detect the progression of neurodegenerative pathologies before they cause irreversible damage to the brain. One of the key objectives of her research is to develop validated biomarkers of neurodegeneration. These markers could be used for early diagnosis, initiating prevention strategies for those at risk, monitoring the efficacy and regional specificity of therapies, and clinical trial enrichment. She has over 20 years of experience in developing algorithmic approaches for the analysis of multi-disciplinary and multi-modality data, including neuroimages, fluid biomarkers, genetics, proteomics, and cognitive measures, all within a unified framework. Her work is characterized by inter-disciplinarity, as she has applied her computational expertise in an engineering framework to facilitate both clinical neuroscience research studies and clinical trials on Alzheimer’s Disease and related dementias. Her research has been peer-funded by various sources, including the National Institute of Aging, Department of Defense, Michael J Fox Foundation, Alzheimer's Associations, and several industry partners and pharmaceutical collaborations. She has held various roles in collaborative projects, including serving as a Co-Investigator of ADNI, leading the ADNI MRI Core’s efforts on processing of structural and ASL MRIs, and serving as the PI of the ADNI4 Project on the role of imaging and fluid biomarkers in Alzheimer’s disease clinical trials. Additionally, She is a Co-Investigator/Site-PI/Core-Lead in various multicenter collaborative projects such as NIA R01AG058676: Alzheimer's dementia onset and progression in international cohorts; NIA U01AG068057-01: Ultrascale Machine Learning to Empower Discovery in Alzheimer’s Disease Biobanks; NIA U24AG057437 Alzheimer's Clinical Trials Consortium – ACTC; U24 AG074855: Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium. She brings extensive experience in the development and validation of biomarkers for Alzheimer’s Disease clinical trials and has previously led multiple projects on biomarker development in neurodegenerative conditions.
This keynote is part of the Image Processing conference.
9:20 AM - 10:00 AM:
Wearable ultrasound technology
Sheng Xu, Univ. of California, San Diego (United States)
Wearable electronic devices that continuously and noninvasively monitor vital signs have become a transformative trend in healthcare. Advances in materials design and microfabrication techniques have enabled the seamless integration of sensors and components onto soft, flexible platforms that conform to the body, allowing for real-time health data collection with minimal impact on daily activities. These systems enable continuous monitoring, making them highly valuable for proactive health management. A key advantage of wearable ultrasound technology lies in its ability to capture physiological signals from deep tissues, which provide more accurate and timely information on internal processes than traditional surface-level measurements. This makes it particularly useful for monitoring critical internal functions with greater precision. In this presentation, I will showcase a novel soft ultrasonic system that can noninvasively and continuously acquire dynamic information from deep tissues and central organs. The technology enables high-resolution recording of blood pressure and flow waveforms in central vessels, precise monitoring of cardiac chamber activities, and accurate measurement of core body temperatures. These features make it an invaluable tool for various healthcare applications, including clinical practice, where it could enhance patient monitoring, and defense medicine, where real-time vital sign tracking is critical in field settings. Furthermore, the platform's adaptability suggests significant potential for integration into consumer electronics, advancing personalized health monitoring. This soft ultrasonic technology represents a versatile platform poised to transform applications in clinical practice, defense, and everyday healthcare, improving outcomes and fostering the shift toward more continuous, noninvasive monitoring solutions.
Sheng Xu is a Professor and Jacobs Faculty Scholar at UC San Diego. He earned his B.S. degree in Chemistry from Peking University and his Ph.D. in Materials Science and Engineering from the Georgia Institute of Technology. Subsequently, he pursued postdoctoral studies at the Materials Research Laboratory at the University of Illinois at Urbana-Champaign. His research group is interested in developing new materials and fabrication methods for soft electronics, with a particular focus on wearable ultrasound technology. His research has been presented to the United States Congress as a testimony to the importance and impact of funding from the National Institutes of Health. He has received numerous honors, including the NIH Maximizing Investigators’ Research Award, NIH Trailblazer Award, Sloan Fellowship, IEEE EMBS Technical Achievement Award, ETH Zürich Materials Research Prize for Young Investigators, MRS Outstanding Early Career Investigator Award, and a finalist of the Blavatnik National Awards for Young Scientists. He is an AIMBE Fellow.
This keynote is part of the Ultrasonic Imaging and Tomography conference.
Event Details
FORMAT: General session with live audience Q&A to follow each presentation.MENU: Coffee, decaf, and tea will be available outside presentation room.
SETUP: Assortment of classroom and theater style seating.