Plenary Event
Tuesday Morning Keynotes
21 February 2023 • 8:30 AM - 10:00 AM PST | Town & Country A
Session Chairs: Olivier Colliot, Ctr. National de la Recherche Scientifique (France) and Claudia R. Mello-Thoms, Univ. Iowa Carver College of Medicine (United States)
8:30 AM:
Welcome and Introduction
8:35 AM:
Robert F. Wagner Award Finalists Announcements for Conferences 12464 and 12467
Image Processing Student Paper Award Announcement
Award Sponsored by:
8:40 AM
ENIGMA, big data, & the human brain: worldwide neuroimaging & genomics of 30 brain diseases in 100,000 people from 45 countries
Paul M. Thompson, University of Southern California (United States)
Since 2009, we have led the ENIGMA Consortium, a worldwide alliance of over 2,000 scientists studying 30 brain diseases in 45 countries. Pooling multimodal brain images and genomic data from over 100,000 people worldwide, ENIGMA's 51 working groups have published the largest neuroimaging studies of schizophrenia, bipolar disorder, depression, PTSD, addiction, and Parkinson’s disease, OCD, ADHD, epilepsy, HIV and autism. ENIGMA’s genomic screens of more than 70,000 people’s brain scans and genome-wide data have brought together experts from 300 institutions to unearth genetic variants that affect brain structure, connectivity, functional brain synchrony, and disease risk. In this talk, we cover current and future challenges in analyzing medical imaging and genomic data worldwide. We describe the vast power of AI and deep learning methods for disease diagnosis, subtyping, and staging, and for discovering environmental, medication, and genomic factors that promote or resist disease. We illustrate the talk with mathematical examples from meta-analysis, AI and federated algorithms for multimodal image harmonization, predictive modeling, and even novel image synthesis and enhancement.
For over 20 years, Paul Thompson and his team of collaborators have been pioneering the field of brain imaging. Dr. Thompson directs the ENIGMA Consortium, a global alliance of 307 scientists in 33 countries who conduct the largest studies of 10 major brain diseases, ranging from schizophrenia, depression, ADHD, bipolar illness and OCD, to HIV and the effects of addictions on the brain. ENIGMA’s genomic screens of more than 31,000 people’s brain scans and genome-wide data have brought together experts from 185 institutions to unearth genetic variants that affect brain structure, disease risk, and brain connectivity. Dr. Thompson will initiate studies involving ocular imaging, brain imaging, genetics, brain development particularly as it relates to amblyopia and other eye diseases. Dr. Paul Thompson graduated from Oxford University, England with a B.A and M.A. in mathematics. He then earned a PhD in neuroscience at the Brain Research institute, Division of Brain Mapping and laboratory of Neuro Imaging, UCLA. Dr. Thompson has over 600 hundred publications, receiving numerous awards and honors. He has served as Associated Editor of several academic journals such as, Human Brain Mapping, NeuroImag and Transactions on Medical Imaging. He was also elected to the prestigious American Neurological Association in 2007.
This keynote is part of the Image Processing conference.
9:20 AM
Human-AI collaboration
Mark Steyvers, Univ. of California, Irvine (United States)
Artificial intelligence (AI) and machine learning models are being increasingly deployed in real-world applications including medical imaging. In many of these applications, there is strong motivation to develop hybrid systems in which humans and AI algorithms can work together, leveraging their complementary strengths and weaknesses. In this talk, I will discuss the promises and pitfalls of AI-assisted decision-making where a human decision-maker is aided by an AI. I will present empirical research that investigates the effectiveness of AI-assisted decisions and the cognitive decision process in different paradigms for presenting AI advice. I will also discuss the question of "machine theory of mind" and "theory of machine," how humans and machines can efficiently form mental models of each other to collaborate more effectively.
Mark Steyvers' research interests span a diverse set of topics in cognitive science such as wisdom of crowds, episodic and semantic memory, dynamic decision making, and causal reasoning. In each of these areas, he combines mathematical and computational modeling with behavioral experiments. The models and experiments are tightly coupled: he tries to formulate empirical questions with the goals of constraining, developing, or testing between alternative computational models of how people learn, process, and represent information. His research interests also include some computer science topics in the domain of statistical machine learning and information retrieval. The adoption of recent machine learning methodology has helped him in advancing cognitive science research, especially in the area of semantic memory.
This keynote is part of the Image Perception, Observer Performance, and Technology Assessment conference.
8:30 AM:
Welcome and Introduction
8:35 AM:
Robert F. Wagner Award Finalists Announcements for Conferences 12464 and 12467
Image Processing Student Paper Award Announcement
Award Sponsored by:
8:40 AM
ENIGMA, big data, & the human brain: worldwide neuroimaging & genomics of 30 brain diseases in 100,000 people from 45 countries
Paul M. Thompson, University of Southern California (United States)
Since 2009, we have led the ENIGMA Consortium, a worldwide alliance of over 2,000 scientists studying 30 brain diseases in 45 countries. Pooling multimodal brain images and genomic data from over 100,000 people worldwide, ENIGMA's 51 working groups have published the largest neuroimaging studies of schizophrenia, bipolar disorder, depression, PTSD, addiction, and Parkinson’s disease, OCD, ADHD, epilepsy, HIV and autism. ENIGMA’s genomic screens of more than 70,000 people’s brain scans and genome-wide data have brought together experts from 300 institutions to unearth genetic variants that affect brain structure, connectivity, functional brain synchrony, and disease risk. In this talk, we cover current and future challenges in analyzing medical imaging and genomic data worldwide. We describe the vast power of AI and deep learning methods for disease diagnosis, subtyping, and staging, and for discovering environmental, medication, and genomic factors that promote or resist disease. We illustrate the talk with mathematical examples from meta-analysis, AI and federated algorithms for multimodal image harmonization, predictive modeling, and even novel image synthesis and enhancement.
For over 20 years, Paul Thompson and his team of collaborators have been pioneering the field of brain imaging. Dr. Thompson directs the ENIGMA Consortium, a global alliance of 307 scientists in 33 countries who conduct the largest studies of 10 major brain diseases, ranging from schizophrenia, depression, ADHD, bipolar illness and OCD, to HIV and the effects of addictions on the brain. ENIGMA’s genomic screens of more than 31,000 people’s brain scans and genome-wide data have brought together experts from 185 institutions to unearth genetic variants that affect brain structure, disease risk, and brain connectivity. Dr. Thompson will initiate studies involving ocular imaging, brain imaging, genetics, brain development particularly as it relates to amblyopia and other eye diseases. Dr. Paul Thompson graduated from Oxford University, England with a B.A and M.A. in mathematics. He then earned a PhD in neuroscience at the Brain Research institute, Division of Brain Mapping and laboratory of Neuro Imaging, UCLA. Dr. Thompson has over 600 hundred publications, receiving numerous awards and honors. He has served as Associated Editor of several academic journals such as, Human Brain Mapping, NeuroImag and Transactions on Medical Imaging. He was also elected to the prestigious American Neurological Association in 2007.
This keynote is part of the Image Processing conference.
9:20 AM
Human-AI collaboration
Mark Steyvers, Univ. of California, Irvine (United States)
Artificial intelligence (AI) and machine learning models are being increasingly deployed in real-world applications including medical imaging. In many of these applications, there is strong motivation to develop hybrid systems in which humans and AI algorithms can work together, leveraging their complementary strengths and weaknesses. In this talk, I will discuss the promises and pitfalls of AI-assisted decision-making where a human decision-maker is aided by an AI. I will present empirical research that investigates the effectiveness of AI-assisted decisions and the cognitive decision process in different paradigms for presenting AI advice. I will also discuss the question of "machine theory of mind" and "theory of machine," how humans and machines can efficiently form mental models of each other to collaborate more effectively.
Mark Steyvers' research interests span a diverse set of topics in cognitive science such as wisdom of crowds, episodic and semantic memory, dynamic decision making, and causal reasoning. In each of these areas, he combines mathematical and computational modeling with behavioral experiments. The models and experiments are tightly coupled: he tries to formulate empirical questions with the goals of constraining, developing, or testing between alternative computational models of how people learn, process, and represent information. His research interests also include some computer science topics in the domain of statistical machine learning and information retrieval. The adoption of recent machine learning methodology has helped him in advancing cognitive science research, especially in the area of semantic memory.
This keynote is part of the Image Perception, Observer Performance, and Technology Assessment conference.