![Mini-Grand Rounds - Tina Hernandez-Boussard, MPH, PhD @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/03/tina-hernandez-boussard-300x300.jpg)
Mini-Grand Rounds: COVID-19: Meeting the Challenge with Data Science
Tina Hernandez-Boussard, MPH, PhD
Professor, Radiology
Stanford University
7:00am – 7:30am, Zoom
The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.
![Mini-Grand Rounds - Colin Kahl, PhD @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/03/colin-kahl-300x271.jpg)
Mini-Grand Rounds: Aftershocks: The Coronavirus Pandemic and The New World Disorder
Colin H. Kahl
Senior Fellow at the Freeman Spogli Institute for International Studies
Steven C. Házy Senior Fellow at the Center for International Security and Cooperation
Professor, by courtesy, of Political Science
Co-director of the Center for International Security and Cooperation
7:00am – 7:30am, Zoom
The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.
![CANCELLED - IMAGinING THE FUTURE - Elias Zerhouni, M.D. @ CANCELLED](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/Zerhouni_photo-300x217.jpeg)
Please note this seminar is now cancelled and will be rescheduled for a future date. Please contact Ashley Williams (ashleylw@stanford.edu) with any questions or concerns. Thank you for your understanding!
IMAGinING THE FUTURE: “Journey Through Academia, Government and Industry: Lessons Learned”
Elias Zerhouni, M.D.
Professor Emeritus
John Hopkins University
![Mini-Grand Rounds - Nicholas Bloom, PhD @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/03/nicholas-bloom.jpg)
Mini-Grand Rounds: The short-run challenges and long-run opportunities of working from home
Nicholas Bloom, PhD
Professor (by courtesy), Economics
Senior Fellow, Stanford Institute for Economic Policy Research
7:00am – 7:30am, Zoom
The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.
![IBIIS/AIMI Seminar - Tiwari @ ZOOM - See Description for Zoom link](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/04/ibiis-logo-1-300x188.jpg)
Radiomics and Radio-Genomics: Opportunities for Precision Medicine
Zoom: https://stanford.zoom.us/j/99904033216?pwd=U2tTdUp0YWtneTNUb1E4V2x0OTFMQT09
Pallavi Tiwari, PhD
Assistant Professor of Biomedical Engineering
Associate Member, Case Comprehensive Cancer Center
Director of Brain Image Computing Laboratory
School of Medicine | Case Western Reserve University
Abstract:
In this talk, Dr. Tiwari will focus on her lab’s recent efforts in developing radiomic (extracting computerized sub-visual features from radiologic imaging), radiogenomic (identifying radiologic features associated with molecular phenotypes), and radiopathomic (radiologic features associated with pathologic phenotypes) techniques to capture insights into the underlying tumor biology as observed on non-invasive routine imaging. She will focus on clinical applications of this work for predicting disease outcome, recurrence, progression and response to therapy specifically in the context of brain tumors. She will also discuss current efforts in developing new radiomic features for post-treatment evaluation and predicting response to chemo-radiation treatment. Dr. Tiwari will conclude with a discussion on her lab’s findings in AI + experts, in the context of a clinically challenging problem of post-treatment response assessment on routine MRI scans.
![Mini-Grand Rounds - Ann Leung, MD @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/03/ann-leung-226x300.jpg)
Mini-Grand Rounds: Stanford University Medical Center and COVID-19: A Chest Radiologist’s Perspective
Ann Leung, MD
Associate Chair, Clinical Affairs
Professor, Radiology
7:00am – 7:30am, Zoom
The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.
![Mini-Grand Rounds - David Larson, MD, MBA @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/03/david-larson-300x300.jpg)
Mini-Grand Rounds: The Outlook for Radiology in the Next Phases of the Pandemic and Beyond
David Larson, MD, MBA
Vice Chair, Education and Clinical Operations
Associate Professor, Radiology
7:00am – 7:30am, Zoom
The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.
Ge Wang, PhD
Clark & Crossan Endowed Chair Professor
Director of the Biomedical Imaging Center
Rensselaer Polytechnic Institute
Troy, New York
Abstract:
AI-based tomography is an important application and a new frontier of machine learning. AI, especially deep learning, has been widely used in computer vision and image analysis, which deal with existing images, improve them, and produce features. Since 2016, deep learning techniques are actively researched for tomography in the context of medicine. Tomographic reconstruction produces images of multi-dimensional structures from externally measured “encoded” data in the form of various transforms (integrals, harmonics, and so on). In this presentation, we provide a general background, highlight representative results, and discuss key issues that need to be addressed in this emerging field.
About:
AI-based X-ray Imaging System (AXIS) lab is led by Dr. Ge Wang, affiliated with the Department of Biomedical Engineering at Rensselaer Polytechnic Institute and the Center for Biotechnology and Interdisciplinary Studies in the Biomedical Imaging Center. AXIS lab focuses on innovation and translation of x-ray computed tomography, optical molecular tomography, multi-scale and multi-modality imaging, and AI/machine learning for image reconstruction and analysis, and has been continuously well funded by federal agencies and leading companies. AXIS group collaborates with Stanford, Harvard, Cornell, MSK, UTSW, Yale, GE, Hologic, and others, to develop theories, methods, software, systems, applications, and workflows.
![Racial Equity Challenge: Race in society @ Zoom](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/04/shield.png)
Targeted violence continues against Black Americans, Asian Americans, and all people of color. The department of radiology diversity committee is running a racial equity challenge to raise awareness of systemic racism, implicit bias and related issues. Participants will be provided a list of resources on these topics such as articles, podcasts, videos, etc., from which they can choose, with the “challenge” of engaging with one to three media sources prior to our session (some videos are as short as a few minutes). Participants will meet in small-group breakout sessions to discuss what they’ve learned and share ideas.
Please reach out to Marta Flory, flory@stanford.edu with questions. For details about the session, including recommended resources and the Zoom link, please reach out to Meke Faaoso at mfaaoso@stanford.edu.
![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