![SMMR Panel Discussion: Mixed Reality for Surgical Guidance @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/03/immers-300x198.png)
Mixed Reality for Surgical Guidance will take place on Thursday, April 1st from 9:00 – 10:30 am PDT.
The event will start with a one-hour panel discussion featuring Dr. Bruce Daniel of Stanford Radiology and the Stanford IMMERS Lab; Christoffer Hamilton of Brainlab, a surgical software and hardware leader in Germany; and Dr. Thomas Grégory of Orthopedic Surgery at the Université Sorbonne Paris Nord.
This panel will be moderated by Dr. Christoph Leuze of Stanford University and the Stanford Medical Mixed Reality (SMMR) program.
Immediately following the panel discussion, you are also invited to a 30-minute interactive session with the panelists where questions and ideas can be explored in real time.
Register here: https://stanford.zoom.us/meeting/register/tJcqf-GrqToiHNKL4D-5haRLowQylIwMEAve
![Cancer Early Detection Seminar Series - Michael Berger, Ph.D. @ Zoom - See Description for Zoom Link](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/berger_160204_07-2_3x2-300x200.jpg)
CEDSS: “Building a Scalable Clinical Genomics Program: How tumor, normal, and plasma DNA sequencing are informing cancer care, cancer risk, and cancer detection”
Elizabeth and Felix Rohatyn Chair & Associate Director of the Marie-Josée and Henry R. Kravis Center for Molecular Oncology
Memorial Sloan Kettering Cancer Center
Zoom Details
Meeting URL: https://stanford.zoom.us/s/92559505314
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Meeting ID: 925 5950 5314
Passcode: 418727
11:00am – 12:00pm Seminar & Discussion
RSVP Here
ABSTRACT
Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of oncogenomic mutations that can be targeted therapeutically. To accelerate enrollment to clinical trials of molecularly targeted agents and guide treatment selection, we have established a center-wide, prospective clinical sequencing program at Memorial Sloan Kettering Cancer Center using a custom, paired tumor-blood normal sequencing assay (MSK-IMPACT), which we have used to profile more than 50,000 patients with solid tumors. Yet beyond just the characterization of tumor-specific alterations, the inclusion of blood DNA has readily enabled the identification of germline risk alleles and somatic mutations associated with clonal hematopoiesis. To complement this approach, we have also implemented a ‘liquid biopsy’ cfDNA panel (MSK-ACCESS) for cancer detection, surveillance, and treatment selection and monitoring. In my talk, I will describe the prevalence of somatic and germline genomic alterations in a real-world population, the clinical benefits of cfDNA assessment, and how clonal hematopoiesis can inform cancer risk and confound liquid biopsy approaches to cancer detection.
ABOUT
Michael Berger, PhD, holds the Elizabeth and Felix Rohatyn Chair and is Associate Director of the Marie-Josée and Henry R. Kravis Center for Molecular Oncology at Memorial Sloan Kettering Cancer Center, a multidisciplinary initiative to promote precision oncology through genomic analysis to guide the diagnosis and treatment of cancer patients. He is also an Associate Attending Geneticist in the Department of Pathology with expertise in cancer genomics, computational biology, and high-throughput DNA sequencing technology. His laboratory is developing experimental and computational methods to characterize the genetic makeup of individual cancers and identify genomic biomarkers of drug response and resistance. As Scientific Director of Clinical NGS in the Molecular Diagnostics Service, he oversees the development and bioinformatics associated with clinical sequencing assays, and he helped lead the development and implementation of MSK-IMPACT, a comprehensive FDA-authorized tumor sequencing panel that been used to profile more than 60,000 tumors from advanced cancer patients at MSK. The resulting data have enabled the characterization of somatic and germline biomarkers across many cancer types and the identification of mutations associated with clonal hematopoiesis. Dr. Berger also led the development of a clinically validated plasma cell-free DNA assay, MSK-ACCESS, which his laboratory is using to explore tumor evolution, acquired drug resistance, and occult metastatic disease. He received his Bachelor’s Degree in Physics from Princeton University and his Ph.D. in Biophysics from Harvard University.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by: The Canary Center & the Department of Radiology
Stanford University – School of Medicine
![IMMERS - Stanford Medical Mixed Reality Panel Discussion Series @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/logo_friendly_small.png)
Join us for a panel on Behavioral XR on Thursday, June 3rd from 9:00 – 10:30 am PDT. The event will start with a one-hour panel discussion featuring Dr. Elizabeth McMahon, a psychologist with a private practice in California; Sarah Hill of Healium, a company developing XR apps for mental fitness based in Missouri; Christian Angern of Sympatient, a company developing VR for anxiety therapy based in Germany; and Marguerite Manteau-Rao of Penumbra, a medical device company based in California. This panel will be moderated by Dr. Walter Greenleaf of Stanford’s Virtual Human Interaction Lab (VHIL) and Dr. Christoph Leuze of the Stanford Medical Mixed Reality (SMMR) program. Immediately following the panel discussion, you are also invited to a 30-minute interactive session with the panelists where questions and ideas can be explored in real time.
Register here to save your place now! After registering, you will receive a confirmation email containing information about joining the meeting.
Please visit this page to subscribe to our events mailing list.
Sponsored by Stanford Medical Mixed Reality (SMMR)
![International Conference on Functional Imaging and Modeling of the Heart @ Virtual Event](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/FIMH_sidebar_logo.jpg)
Join us for the 11th biennial International Conference on Functional Imaging and Modeling of the Heart (FIMH). FIMH-2021 will celebrate 20 years of bringing together friends, colleagues, and collaborators to share and discuss the latest in cardiac and cardiovascular imaging, electrophysiology, computational modeling, and translational applications. The event will take place June 21-25, 2021 virtually, via Livestream, Zoom meeting workshops, and Spatial Chat networking.
Sponsored by: Functional Imaging and Modeling of the Heart Conference
![Radiology-Wide Research Conference @ Zoom – Details can be found here: https://radresearch.stanford.edu](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/07/RWRC-July-300x195.jpeg)
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
![2021 AIMI Symposium + BOLD-AIR Summit @ Virtual Livestream](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/2021-Symposium-and-BOLD-Banner_06182121-300x112.png)
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 - Simon Cherry, PhD @ LKSC 101/102 & Zoom - See Description for Zoom Link](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/07/simon_cherry_website-269x300.jpg)
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
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
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 - Jennifer L. Eberhardt, PhD @ Zoom - See Description for Zoom Link](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/07/download.jpg)
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.