Calendar

Apr
20
Mon
2020
Mini-Grand Rounds - Colin Kahl, PhD @ Zoom
Mini-Grand Rounds – Colin Kahl, PhD
Apr 20 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Colin Kahl, PhD @ Zoom

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.

Apr
22
Wed
2020
CANCELLED - IMAGinING THE FUTURE - Elias Zerhouni, M.D. @ CANCELLED
CANCELLED – IMAGinING THE FUTURE – Elias Zerhouni, M.D.
Apr 22 @ 1:00 pm – 2:30 pm CANCELLED
CANCELLED - IMAGinING THE FUTURE - Elias Zerhouni, M.D. @ CANCELLED

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
Mini-Grand Rounds – Nicholas Bloom, PhD
Apr 22 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Nicholas Bloom, PhD @ Zoom

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
IBIIS/AIMI Seminar – Tiwari
Apr 22 @ 1:00 pm – 2:00 pm ZOOM - See Description for Zoom link
IBIIS/AIMI Seminar - Tiwari @ ZOOM - See Description for Zoom link

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.

Apr
24
Fri
2020
Mini-Grand Rounds - Ann Leung, MD @ Zoom
Mini-Grand Rounds – Ann Leung, MD
Apr 24 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Ann Leung, MD @ Zoom

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.

Apr
27
Mon
2020
Mini-Grand Rounds - David Larson, MD, MBA @ Zoom
Mini-Grand Rounds – David Larson, MD, MBA
Apr 27 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - David Larson, MD, MBA @ Zoom

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.

Sep
16
Wed
2020
IBIIS & AIMI Seminar - Judy Gichoya, MD @ Zoom - See Description for Zoom Link
IBIIS & AIMI Seminar – Judy Gichoya, MD
Sep 16 @ 12:00 pm – 1:00 pm Zoom - See Description for Zoom Link
IBIIS & AIMI Seminar - Judy Gichoya, MD @ Zoom - See Description for Zoom Link

Judy Gichoya, MD
Assistant Professor
Emory University School of Medicine

Measuring Learning Gains in Man-Machine Assemblage When Augmenting Radiology Work with Artificial Intelligence

Abstract
The work setting of the future presents an opportunity for human-technology partnerships, where a harmonious connection between human-technology produces unprecedented productivity gains. A conundrum at this human-technology frontier remains – will humans be augmented by technology or will technology be augmented by humans? We present our work on overcoming the conundrum of human and machine as separate entities and instead, treats them as an assemblage. As groundwork for the harmonious human-technology connection, this assemblage needs to learn to fit synergistically. This learning is called assemblage learning and it will be important for Artificial Intelligence (AI) applications in health care, where diagnostic and treatment decisions augmented by AI will have a direct and significant impact on patient care and outcomes. We describe how learning can be shared between assemblages, such that collective swarms of connected assemblages can be created. Our work is to demonstrate a symbiotic learning assemblage, such that envisioned productivity gains from AI can be achieved without loss of human jobs.

Specifically, we are evaluating the following research questions: Q1: How to develop assemblages, such that human-technology partnerships produce a “good fit” for visually based cognition-oriented tasks in radiology? Q2: What level of training should pre-exist in the individual human (radiologist) and independent machine learning model for human-technology partnerships to thrive? Q3: Which aspects and to what extent does an assemblage learning approach lead to reduced errors, improved accuracy, faster turn-around times, reduced fatigue, improved self-efficacy, and resilience?

Zoom: https://stanford.zoom.us/j/93580829522?pwd=ZVAxTCtEdkEzMWxjSEQwdlp0eThlUT09

Nov
18
Wed
2020
IBIIS & AIMI Seminar: Deep Tomographic Imaging @ Zoom: https://stanford.zoom.us/j/96731559276?pwd=WG5zcEFwSGlPcDRsOUFkVlRhcEs2Zz09
IBIIS & AIMI Seminar: Deep Tomographic Imaging
Nov 18 @ 12:00 pm – 1:00 pm Zoom: https://stanford.zoom.us/j/96731559276?pwd=WG5zcEFwSGlPcDRsOUFkVlRhcEs2Zz09

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.

Apr
30
Fri
2021
Racial Equity Challenge: Race in society @ Zoom
Racial Equity Challenge: Race in society
Apr 30 @ 12:00 pm – 1:00 pm Zoom
Racial Equity Challenge: Race in society @ Zoom

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.

Jul
16
Fri
2021
Radiology-Wide Research Conference @ Zoom – Details can be found here: https://radresearch.stanford.edu
Radiology-Wide Research Conference
Jul 16 @ 12:00 pm – 1:00 pm Zoom – Details can be found here: https://radresearch.stanford.edu
Radiology-Wide Research Conference @ Zoom – Details can be found here: https://radresearch.stanford.edu

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