Radiology Department-Wide Research Meeting
• Research Announcements
• Mirabela Rusu, PhD – Learning MRI Signatures of Aggressive Prostate Cancer: Bridging the Gap between Digital Pathologists and Digital Radiologists
• Akshay Chaudhari, PhD – Data-Efficient Machine Learning for Medical Imaging
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
Meetings will be the 3rd Friday of each month.
Hosted by: Kawin Setsompop, PhD
Sponsored by: the the Department of Radiology
Stanford AIMI Director Curt Langlotz and Co-Directors Matt Lungren and Nigam Shah invite you to join us on August 3 for the 2021 Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI) Symposium. The virtual symposium will focus on the latest, best research on the role of AI in diagnostic excellence across medicine, current areas of impact, fairness and societal impact, and translation and clinical implementation. The program includes talks, interactive panel discussions, and breakout sessions. Registration is free and open to all.
Also, the 2nd Annual BiOethics, the Law, and Data-sharing: AI in Radiology (BOLD-AIR) Summit will be held on August 4, in conjunction with the AIMI Symposium. The summit will convene a broad range of speakers in bioethics, law, regulation, industry groups, and patient safety and data privacy, to address the latest ethical, regulatory, and legal challenges regarding AI in radiology.
CME Grand Rounds Sanjiv Sam Gambhir Lectureship – “Imaging at the Speed of Light: Innovations in Positron Emission Tomography”
Simon R. Cherry, PhD
Professor
Biomedical Engineering & Radiology
UC Davis
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
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International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Positron emission tomography (PET) allows for sensitive and quantitative measurement of physiology, metabolism and molecular targets noninvasively in the human body. However, typical clinical PET scanners capture less than 1% of the available signal produced in the body. PET scanners also are not currently capable of precisely determining the location at which a particular decay occurs. These limitations present opportunities for further innovation that ultimately will impact molecular imaging research and diagnostic imaging with PET. This presentation focuses on 1) total-body PET imaging which greatly improves signal collection, allowing radiotracer kinetics to be assessed across the entire human body for the first time, and 2) the development of detector technologies that have a timing precision of ~ 30 picoseconds, enabling direct localization of radiotracer decays without tomographic reconstruction.
BIO
Simon R. Cherry, Ph.D. received his B.Sc.(Hons) in Physics with Astronomy from University College London in 1986 and a Ph.D. in Medical Physics from the Institute of Cancer Research, University of London in 1989. After a postdoctoral fellowship at UCLA, he joined the faculty in the Department of Molecular and Medical Pharmacology, also at UCLA, in 1993. In 2001, Dr. Cherry joined UC Davis and established the Center for Molecular and Genomic Imaging, which he directed from 2004-2016. Currently Dr. Cherry is Distinguished Professor in the Departments of Biomedical Engineering and Radiology at UC Davis.
Dr. Cherry’s research interests center around biomedical imaging and in particular the development and application of in vivo molecular imaging systems. His major accomplishments have been in developing systems for positron emission tomography (PET), in particular the invention of the microPET technology that was subsequently widely adopted in academia and industry and as co-leader of the EXPLORER consortium which has developed the world’s first total-body PET scanner. He also has contributed to detector technology innovations for PET, conducted early biomedical studies using Cerenkov luminescence, and developed the first proof-of-concept hybrid PET/MRI (magnetic resonance imaging) systems.
Dr. Cherry is a founding member of the Society of Molecular Imaging and an elected fellow of six professional societies, including the Institute for Electronic and Electrical Engineers (IEEE) and the Biomedical Engineering Society (BMES). He served as Editor-in-Chief of the journal Physics in Medicine and Biology from 2011-2020. Dr. Cherry received the Academy of Molecular Imaging Distinguished Basic Scientist Award (2007), the Society for Molecular Imaging Achievement Award (2011) and the IEEE Marie Sklodowska-Curie Award (2016). In 2016, he was elected as a member of the National Academy of Engineering and in 2017 he was elected to the National Academy of Inventors. Dr. Cherry is the author of more than 240 peer-reviewed journal articles, review articles and book chapters in the field of biomedical imaging. He is also lead author of the widely-used textbook “Physics in Nuclear Medicine”.
Regina Barzilay, PhD
School of Engineering Distinguished Professor for AI and Health
Electrical Engineering and Computer Science Department
AI Faculty Lead at Jameel Clinic for Machine Learning in Health
Computer Science and Artificial Intelligence Lab
Massachusetts Institute of Technology
Abstract:
In this talk, I will present methods for future cancer risk from medical images. The discussion will explore alternative ways to formulate the risk assessment task and focus on algorithmic issues in developing such models. I will also discuss our experience in translating these algorithms into clinical practice in hospitals around the world.
CME Grand Rounds Diversity Lectureship – Topic: TBD
Jennifer L. Eberhardt, PhD
Professor
Psychology
Stanford University
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
Keynote:
Self-Supervision for Learning from the Bottom Up
Why do self-supervised learning? A common answer is: “because data labeling is expensive.” In this talk, I will argue that there are other, perhaps more fundamental reasons for working on self-supervision. First, it should allow us to get away from the tyranny of top-down semantic categorization and force meaningful associations to emerge naturally from the raw sensor data in a bottom-up fashion. Second, it should allow us to ditch fixed datasets and enable continuous, online learning, which is a much more natural setting for real-world agents. Third, and most intriguingly, there is hope that it might be possible to force a self-supervised task curriculum to emerge from first principles, even in the absence of a pre-defined downstream task or goal, similar to evolution. In this talk, I will touch upon these themes to argue that, far from running its course, research in self-supervised learning is only just beginning.
CME Grand Rounds – “Community Based Partnered Research: Revisiting a Critical Concept for Radiology”
Christoph L. Lee, MD, MS, MBA
Professor
Radiology
University of Washington
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
CME Grand Rounds – Topic: TBD
Jocelyn D. Chertoff, MD, MS
Professor
Radiology, Obstetrics & Gynecology
Chair, Radiology
Dartmouth Hitchcock Medical Center
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
CME Grand Rounds Etta K. Moskowitz Lectureship – Topic: TBD
Elizabeth Krupinski, PhD
Professor & Vice Chair for Research
Radiology & Imaging Sciences
Emory University School of Medicine
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
CME Grand Rounds – “Promote Your Academic Career Using Social Media”
Michael Gisondi, MD
Associate Professor & Vice Chair of Education
Emergency Medicine
Stanford University
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!