BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//171.67.215.200//NONSGML kigkonsult.se iCalcreator 2.26.9//
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-FROM-URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar
X-WR-TIMEZONE:America/Los_Angeles
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
X-LIC-LOCATION:America/Los_Angeles
BEGIN:STANDARD
DTSTART:20231105T020000
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
RDATE:20241103T020000
TZNAME:PST
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20240310T020000
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
RDATE:20250309T020000
TZNAME:PDT
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:ai1ec-2487@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:Annual Conferences\,Radiology
CONTACT:Ashley Williams\; ashleylw@stanford.edu\; https://fimh2021.github.i
o/
DESCRIPTION:
Cancer Resear
ch UK\, OHSU Knight Cancer Institute and the Canary Center at Stanford\, p
resent the Early Detection of Cancer Conference series. The annual Confere
nce brings together experts in early detection from multiple disciplines t
o share ground breaking research and progress in the field.
\nThe Co
nference is part of a long-term commitment to invest in early detection re
search\, to understand the biology behind early stage cancers\, find new d
etection and screening methods\, and enhance uptake and accuracy of screen
ing.
\nTargeted violence co
ntinues against Black Americans\, Asian Americans\, and all people of colo
r. The department of radiology diversity committee is running a racial equ
ity challenge to raise awareness of systemic racism\, implicit bias and re
lated issues. Participants will be provided a list of resources on these t
opics such as articles\, podcasts\, videos\, etc.\, from which they can ch
oose\, with the “challenge” of engaging with one to three media sources pr
ior to our session (some videos are as short as a few minutes). Participan
ts will meet in small-group breakout sessions to discuss what they’ve lear
ned and share ideas.
\nElizabeth and Felix Rohatyn Chair & Associate Director of the Ma
rie-Josée and Henry R. Kravis Center for Molecular Oncology
\nMemoria
l Sloan Kettering Cancer Center
\n<
/div>
MIPS Seminar Series: Image-guided focal therapy f
or prostate cancer
\n
Geoffrey Sonn\, MD
\nAssistant Professor of Urology and\,
by courtesy\, of Radiology (Molecular Imaging Program at Stanford)
\n
Stanford University Medical Center
\n
\n
Location: Zoom
\nWebinar URL: https://stanford.zoom.us/s/96126703618
\nDial: +1 650 724 97
99 or +1 833 302 1536
\nWebinar ID: 961 2670 3618
\nPasscode: 18
6059
\n
12:00pm – 12:45pm Seminar & Discussion
\nRSVP Here
\n
\n
ABSTRACT
\n
In re
cent years\, prostate cancer treatment has increasingly focused on selecti
ng patients who are most likely to benefit and reducing harms from treatme
nt. This has been seen both in adoption of active surveillance for men wit
h low-risk prostate cancer and emergence of image-guided focal ablative th
erapy. While focal therapy causes fewer sexual and urinary side effects th
an conventional prostate cancer treatments\, many questions remain about p
roper patient selection\, treatment planning\, and follow up care.
\n
\n
Improvements in prostate MRI performance and i
nterpretation have paved the way for adoption of focal therapy. However\,
clinical challenges remain in prostate cancer imaging. This talk will desc
ribe prostate cancer focal therapy\, discuss patient selection\, and highl
ight the research efforts of my group to improve MRI interpretation to gui
de biopsy and improve focal therapy performance.
\n
\n
ABOUT
\nGeoffrey Sonn\, MD is a urologic oncologist who spe
cializes in treating patients with prostate and kidney cancer. He has a pa
rticular interest in cancer imaging\, MRI-Ultrasound fusion targeted prost
ate biopsy\, prostate cancer focal therapy\, and robotic surgery for prost
ate and kidney cancer. He is the principal investigator of the first clini
cal trial in Northern California to use MRI-guided focused ultrasound to t
reat prostate cancer. The goal of this trial is to treat prostate cancer w
ith fewer side effects than surgery or radiation.
\n
Dr. Sonn was bor
n in Washington State and lived there until leaving for college at Georget
own. After graduating magna cum laude at Georgetown he returned to the Wes
t Coast for medical school at UCLA. Following medical school\, Dr. Sonn co
mpleted a 6-year urology residency at Stanford where he developed particul
ar interests in the clinical care of patients with urologic cancers and re
search in cancer imaging. Dr. Sonn completed a 2-year urologic oncology fe
llowship at UCLA. Since completing his fellowship\, Dr. Sonn has been at S
tanford as an assistant professor in urology. Dr. Sonn’s research is devot
ed to developing new cancer imaging techniques\, applying artificial intel
ligence to find cancers on medical images\, and applying new methods to tr
eat prostate cancer with fewer side effects.
\n
\n
Hosted
by: Katherine Ferrara\, PhD
\nSponsored by: Molecular Imagin
g Program at Stanford & the Department of Radiology
\n
Tickets:
https://stanford.zoom.
us/webinar/register/8116097828282/WN_mfyC-_dUTwymWGqvmmF1zA.
DTSTART;TZID=America/Los_Angeles:20210527T120000
DTEND;TZID=America/Los_Angeles:20210527T124500
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:MIPS Seminar – Geoffrey Sonn\, MD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/mips-sem
inar-geoffrey-sonn-md/
X-COST-TYPE:external
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/geoffrey-sonn_profilephoto-150x150.jpg
\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcal
endar/wp-content/uploads/2019/10/geoffrey-sonn_profilephoto-300x300.jpg\;3
00\;300\;1\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcalenda
r/wp-content/uploads/2019/10/geoffrey-sonn_profilephoto.jpg\;350\;350\;
X-TICKETS-URL:https://stanford.zoom.us/webinar/register/8116097828282/WN_mf
yC-_dUTwymWGqvmmF1zA
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2627@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:MIPS
CONTACT:Ashley Williams\; ashleylw@stanford.edu
DESCRIPTION:
\n
\n
\n
Molecular Imaging in Neuroscience – MIPS Mini-Retreat
\n
Hosted by: Dr. Michelle L. James
\, PhD
\n
\n
Sponsored by: Department of Radiology\, Molecular Imaging Program at
Stanford
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
The MIPS Mini-retreat series brings together members
of the MIPS and greater School of Medicine community to discuss current o
pportunities for research and collaborations. During each mini-retreat we
will discuss a different topic and we invite all those interested to atten
d. The mini-retreats are roughly two hours in length with ample time for d
iscussion throughout. We hope you can join us and spark new collaborations
!
\n
\n
\n
\n
\n
\n
Zoom Webin
ar Information
\nWebinar URL: https://stanford.zoom.us/j/92903233643
\n
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
\nWebinar I
D: 929 0323 3643
\nPasscode: 146018
\n
\n
Ten
tative Agenda (all times are in PST)
\n8:00-8:0
5 AM – Opening Remarks – Michelle James\, PhD
\n8:05-8:55 AM – Overview and Imaging-based Collaboration: Department of Neurology\, N
eurosurgery\, Pathology\, Psychiatry\, and Nuclear Medicine (Frank M. Longo\, MD\, PhD\, Michael Lim\, MD\, Thomas Montine\, MD\, PhD<
/a>\, Victor G. Car
rión\, MD\, and Guido Davidzon\, MD)
\n8:55-9:20 AM – Faculty I
ntroductions: All interested MIPS faculty on the call give a 2-minute
introduction including their interest in collaborating with Neurology\, Pa
thology\, Neurosurgery\, and/or Psychiatry and Behavioral Sciences departm
ents.
\n9:20-9:40 AM – Recent center proposals
and possible mechanisms: UDALL Collaboration – Michelle James\, PhD and Kathleen Poston\, MD\, MS
\n9:40-10:00 AM – Discussion – Moderated by: Michelle James\, PhD<
/a> and Kath
erine Ferrara\, PhD
DTSTART;TZID=America/Los_Angeles:20210630T080000
DTEND;TZID=America/Los_Angeles:20210630T100000
LOCATION:Virtual Event
SEQUENCE:0
SUMMARY:Molecular Imaging in Neuroscience – MIPS Mini-Retreat
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/molecula
r-imaging-in-neuroscience-mips-mini-retreat/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/Mini-Retreat-Tile_6.30.2021-6-150x150.
jpg\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/Mini-Retreat-Tile_6.30.2021-6-300x205.
jpg\;300\;205\;1
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2803@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI\,IBIIS\,Radiology\,RSL
CONTACT:
DESCRIPTION:
\n
Radiology Department-Wide Research
Meeting
\n
• Research Announcements
\n• Mirabela Rusu\,
PhD – Learning MRI Signatures of Aggressive Prostate Cancer: Bridging the
Gap between Digital Pathologists and Digital Radiologists
\n• Akshay
Chaudhari\, PhD – Data-Efficient Machine Learning for Medical Imaging
\n
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
\nMeetings will be the 3rd F
riday of each month.
\n
\n
Hosted by: Kawin Setsompop\, Ph
D
\nSponsored by: the the Department of Radiology
\n
\n
DTSTART;TZID=America/Los_Angeles:20210716T120000
DTEND;TZID=America/Los_Angeles:20210716T130000
LOCATION:Zoom – Details can be found here: https://radresearch.stanford.edu
SEQUENCE:0
SUMMARY:Radiology-Wide Research Conference
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/radiolog
y-wide-research-conference/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/RWRC-July-150x150.jpeg\;150\;150\;1\,m
edium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content
/uploads/2021/07/RWRC-July-300x195.jpeg\;300\;195\;1\,large\;http://web.st
anford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/07/RWR
C-July.jpeg\;443\;288\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2763@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:Radiology
CONTACT:Ashley Williams\; ashleylw@stanford.edu\; http://radweb.su.domains/
gambhirsymposium/
DESCRIPTION:
Dr.
Sanjiv Sam Gambhir was a visionary who had a profound impact on the world
of science and humanity. As a leader and pioneer in the fields of molecul
ar imaging\, early detection of cancer\, and precision health\, his enduri
ng legacy can be seen in the research and innovations continuing in these
fields today.
\n
The Gambhir Symposium aims to celebrate Dr. Gambhir’
s illustrious career and continue down the paths he forged by highlighting
the work still ongoing in the fields he helped to cultivate. Join us to h
ear researchers and collaborators share current thoughts and future outloo
ks on topics developed with Sam.
\n
We hope you can join us for the 2
021 Virtual Gambhir Symposium.
\n
The event is fully virtual
and the livestream link will be posted on the website closer to the event.
\n
\n
Sponsored by: Department of Radiology at Stanford
\n
Tickets: https://www.onlineregistrationcenter.com/Gambhir2021.<
/p>
DTSTART;TZID=America/Los_Angeles:20210719T083000
DTEND;TZID=America/Los_Angeles:20210719T160000
LOCATION:Virtual Event
SEQUENCE:0
SUMMARY:Gambhir Symposium
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/gambhir-
symposium/
X-COST-TYPE:external
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/calendar-square-150x150.png\;150\;150\
;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-co
ntent/uploads/2019/10/calendar-square-300x205.png\;300\;205\;1
X-TICKETS-URL:https://www.onlineregistrationcenter.com/Gambhir2021
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2809@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI\,Annual Conferences
CONTACT:AIMI Center\; aimicenter@stanford.edu\; https://aimi.stanford.edu/n
ews-events/aimi-symposium/overview
DESCRIPTION:
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 C
enter 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 acro
ss medicine\, current areas of impact\, fairness and societal impact\, and
translation and clinical implementation. The program includes talks\, int
eractive panel discussions\, and breakout sessions. Registration is free a
nd open to all.
\n
\n
Also\, the 2nd Annual BiOethics\, the Law\, and Data-sharing: AI in Radiology (BOLD-AI
R) Summit will be held on August 4\,
in conjunction with the AIMI Symposium. The summit will convene a broad r
ange of speakers in bioethics\, law\, regulation\, industry groups\, and p
atient safety and data privacy\, to address the latest ethical\, regulator
y\, and legal challenges regarding AI in radiology.
\n
\n
REGISTER HERE
\n
Tickets: https://www.eventbrite.com/e/
2021-stanford-aimi-symposium-bold-air-summit-registration-152725816027
.
DTSTART;TZID=America/Los_Angeles:20210803T080000
DTEND;TZID=America/Los_Angeles:20210804T150000
LOCATION:Virtual Livestream
SEQUENCE:0
SUMMARY:2021 AIMI Symposium + BOLD-AIR Summit
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/2021-aim
i-symposium-bold-air-summit/
X-COST-TYPE:external
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/2021-Symposium-and-BOLD-Banner_0618212
1-150x150.png\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/c
gi-bin/radcalendar/wp-content/uploads/2019/10/2021-Symposium-and-BOLD-Bann
er_06182121-300x112.png\;300\;112\;1\,large\;http://web.stanford.edu/group
/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/2021-Symposium-and-
BOLD-Banner_06182121-1024x382.png\;640\;239\;1\,full\;http://web.stanford.
edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/2021-Sympo
sium-and-BOLD-Banner_06182121.png\;1770\;660\;
X-TICKETS-URL:https://www.eventbrite.com/e/2021-stanford-aimi-symposium-bol
d-air-summit-registration-152725816027
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2851@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:CME\,CME Radiology Grand Rounds\,Radiology
CONTACT:Tricia Hatcliff\; 650-498-7359\; thatcliff@stanford.edu
DESCRIPTION:
<
p>CME Grand Rounds Sanjiv Sam Gambhir Lectureship –
“Imaging at the Sp
eed of Light: Innovations in Positron Emission Tomography”\n
\n
Simon R. Cherry\, PhD
\nProfessor
\nBi
omedical Engineering & Radiology
\nUC Davis
\n
\n
Join fr
om PC\, Mac\, Linux\, iOS or Android: https://stanford.zoom.us/j
/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
\nMeeting ID: 600
003 703
\nPassword: 566048
\nOr iPhone one-tap (US Toll): +1833
3021536\,\,600003703# or +16507249799\,\,600003703#
\nOr Telephone:\nDial: +1 650 724 9799 (US\, Canada\, Caribbean Toll) or +1 833 302 1
536 (US\, Canada\, Caribbean Toll Free)
\nInternational numbers avail
able: https://stanford.zoo
m.us/u/acuqphnvqT
\n
\n
ABSTRACT
\n
Positron emission tomography (PET) allows for sensitive and quantitative m
easurement of physiology\, metabolism and molecular targets noninvasively
in the human body. However\, typical clinical PET scanners capture less t
han 1% of the available signal produced in the body. PET scanners also ar
e not currently capable of precisely determining the location at which a p
articular decay occurs. These limitations present opportunities for furthe
r innovation that ultimately will impact molecular imaging research and di
agnostic imaging with PET. This presentation focuses on 1) total-body PET
imaging which greatly improves signal collection\, allowing radiotracer k
inetics to be assessed across the entire human body for the first time\, a
nd 2) the development of detector technologies that have a timing precisio
n of ~ 30 picoseconds\, enabling direct localization of radiotracer decays
without tomographic reconstruction.
\n
\n
BIO
\n
Simon R. Cherry\, Ph.D. received his B.Sc.(Hons) in Physics wit
h Astronomy from University College London in 1986 and a Ph.D. in Medical
Physics from the Institute of Cancer Research\, University of London in 19
89. After a postdoctoral fellowship at UCLA\, he joined the faculty in th
e Department of Molecular and Medical Pharmacology\, also at UCLA\, in 199
3. In 2001\, Dr. Cherry joined UC Davis and established the Center for Mol
ecular and Genomic Imaging\, which he directed from 2004-2016. Currently D
r. Cherry is Distinguished Professor in the Departments of Biomedical Engi
neering and Radiology at UC Davis.
\n
Dr. Cherry’s research interests
center around biomedical imaging and in particular the development and ap
plication 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 subsequent
ly widely adopted in academia and industry and as co-leader of the EXPLORE
R consortium which has developed the world’s first total-body PET scanner.
He also has contributed to detector technology innovations for PET\, con
ducted early biomedical studies using Cerenkov luminescence\, and develope
d the first proof-of-concept hybrid PET/MRI (magnetic resonance imaging) s
ystems.
\n
Dr. Cherry is a founding member of the Society of Molecula
r Imaging and an elected fellow of six professional societies\, including
the Institute for Electronic and Electrical Engineers (IEEE) and the Biome
dical Engineering Society (BMES). He served as Editor-in-Chief of the jour
nal Physics in Medicine and Biology from 2011-2020. Dr. Cherry received th
e 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 membe
r 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 te
xtbook “Physics in Nuclear Medicine”.
DTSTART;TZID=America/Los_Angeles:20210910T120000
DTEND;TZID=America/Los_Angeles:20210910T130000
LOCATION:LKSC 101/102 & Zoom - See Description for Zoom Link @ 291 Campus D
rive\, Stanford\, CA 94305
SEQUENCE:0
SUMMARY:CME Grand Rounds Sanjiv Sam Gambhir Lectureship – Simon Cherry\, Ph
D
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cme-gran
d-rounds-sanjiv-sam-gambhir-lectureship-simon-cherry-phd/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/simon_cherry_website-150x150.jpg\;150\
;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/
wp-content/uploads/2021/07/simon_cherry_website-269x300.jpg\;269\;300\;1\,
large\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content
/uploads/2021/07/simon_cherry_website.jpg\;520\;580\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2989@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; http://ibiis.stan
ford.edu/events/seminars/2021seminars.html
DESCRIPTION:
\n
\n
Regina Barzilay\, PhD
\nScho
ol of Engineering Distinguished Professor for AI and Health
\nElectri
cal Engineering and Computer Science Department
\nAI Faculty Lead at
Jameel Clinic for Machine Learning in Health
\nComputer Science and A
rtificial Intelligence Lab
\nMassachusetts Institute of Technology
\n
Abstract:
\nIn this talk\, I will present meth
ods for future cancer risk from medical images. The discussion will explor
e alternative ways to formulate the risk assessment task and focus on algo
rithmic issues in developing such models. I will also discuss our experien
ce in translating these algorithms into clinical practice in hospitals aro
und the world.
DTSTART;TZID=America/Los_Angeles:20210922T110000
DTEND;TZID=America/Los_Angeles:20210922T120000
LOCATION:Zoom: https://stanford.zoom.us/j/99474772502?pwd=NEQrQUQ0MzdtRjFiY
U42TCs2bFZsUT09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Seeing the Future from Images: ML-Based Model
s for Cancer Risk Assessment
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-seeing-the-future-from-images-ml-based-models-for-cancer-risk-a
ssessment/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/08/regina-300x300.jpeg\;300\;300\,medium\
;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploa
ds/2021/08/regina-300x300.jpeg\;300\;300\,large\;http://web.stanford.edu/g
roup/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/08/regina-300x300.
jpeg\;300\;300\,full\;http://web.stanford.edu/group/radweb/cgi-bin/radcale
ndar/wp-content/uploads/2021/08/regina-300x300.jpeg\;300\;300
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2575@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:MIPS\,MIPS Seminar
CONTACT:Ashley Williams\; ashleylw@stanford.edu\; https://med.stanford.edu/
mips/events.html
DESCRIPTION:
MIPS Seminar Series: Predicting and Prevent
ing Fetal and Neonatal Pathology: Looking Back and Looking Forward
\n
David K. Ste
venson\, MD
\nThe Harold K. Faber Professor of Pediatrics\, Senio
r Associate Dean\, Maternal and Child Health and Professor\, by courtesy\,
of Obstetrics and Gynecology
\nLucile Packard Children’s Hospital
\n
\n
Zoom Webinar Details
\nWebi
nar URL: https://stanford.zoom.us/s/94584828060
\nDial: +1 65
0 724 9799 or +1 833 302 1536
\nWebinar ID: 945 8482 8060
\nPass
code: 481874
\n
12:00pm – 12:45pm Seminar & Discussion
\nRSVP Here
\n
\n
ABSTRACT
\nThe importance of minimally invasive technologies for interrogating the
fetus and newborn\, as well as of knowing where a biologic system is heade
d\, not just where it has been\, when trying to predict and prevent acquir
ed diseases\, will be discussed. Examples of such technologies\, such as
trace gas analysis and optical reporting of biologic phenomena\, and their
application to model systems and the human newborn will be presented. Th
e role of advanced computational approaches for the integration and interp
retation of large amounts of data derived from these new measurement tools
will be emphasized.
\n
\n
ABOUT
\nDr. D
avid K. Stevenson is the Harold K. Faber Professor of Pediatrics and has m
ade many impactful contributions to the field of neonatology and pediatric
s\, including his seminal studies on neonatal jaundice\, bilirubin product
ion and heme oxygenase biology. As a neonatologist\, his research has foc
used primarily on neonatal jaundice and more recently on the causes of pre
term birth and its prevention. He has held numerous leadership roles at S
tanford University School of Medicine\, including Vice Dean and Senior Ass
ociate Dean for Academic Affairs. He is currently the Senior Associate Dea
n for Maternal & Child Health\, the Co-Director of the Stanford Maternal &
Child Health Research Institute\, and the Principal Investigator for the
March of Dimes Prematurity Research Center at Stanford University. Dr. St
evenson has received many awards\, including the Virginia Apgar Award\, wh
ich is the highest award in Perinatal Pediatrics\, the Joseph W. St. Geme\
, Jr. Leadership Award from the Federation of Pediatric Organizations\, th
e Jonas Salk Award for Leadership in Prematurity Prevention from the March
of Dimes Foundation\, and the John Howland Medal and Award\, the highest
award in academic pediatrics. He has served as the President of the Ameri
can Pediatric Society. In recognition of his achievements\, Dr. Stevenson
is a member of the National Academy of Medicine.
\n
\n
Hos
ted by: Katherine Ferrara\, PhD
\nSponsored by: Molecular Im
aging Program at Stanford & the Department of Radiology
\n
Ticke
ts: https://stanford.z
oom.us/webinar/register/7116294064170/WN_H60DZOKZSlWC6UBOB3FTVw.
DTSTART;TZID=America/Los_Angeles:20210923T120000
DTEND;TZID=America/Los_Angeles:20210923T124500
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:MIPS Seminar – David K. Stevenson\, MD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/mips-sem
inar-david-k-stevenson-md/
X-COST-TYPE:external
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/david-stevenson_profilephoto-150x150.j
pg\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radc
alendar/wp-content/uploads/2019/10/david-stevenson_profilephoto-300x300.jp
g\;300\;300\;1\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcal
endar/wp-content/uploads/2019/10/david-stevenson_profilephoto.jpg\;350\;35
0\;
X-TICKETS-URL:https://stanford.zoom.us/webinar/register/7116294064170/WN_H6
0DZOKZSlWC6UBOB3FTVw
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2885@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:CME\,CME Radiology Grand Rounds\,Radiology
CONTACT:Tricia Hatcliff\; 650-498-7359\; thatcliff@stanford.edu
DESCRIPTION:
CME Grand Rounds D
iversity Lectureship – Topic: TBD
\n
\n
Jenni
fer L. Eberhardt\, PhD
\nProfessor
\nPsychology
\n
Stanford University
\n
\n
Join from PC\, Mac\, Linux\, iOS or
Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVk
xyL3U0RmNtUDVWdz09
\nMeeting ID: 600 003 703
\nPassword: 566
048
\nOr iPhone one-tap (US Toll): +18333021536\,\,600003703# or +165
07249799\,\,600003703#
\nOr Telephone:
\nDial: +1 650 724 9799 (
US\, Canada\, Caribbean Toll) or +1 833 302 1536 (US\, Canada\, Caribbean
Toll Free)
\nInternational numbers available: https://stanford.zoom.us/u/acuqphnvqT
\n
\n
ABSTRACT
\nComing soon!
\n
\n
BIO
\nComing soon!
DTSTART;TZID=America/Los_Angeles:20210924T120000
DTEND;TZID=America/Los_Angeles:20210924T130000
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:CME Grand Rounds Diversity Lectureship – Jennifer L. Eberhardt\, Ph
D
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cme-gran
d-rounds-diversity-lectureship-jennifer-l-eberhardt-phd/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/download-150x150.jpg\;150\;150\;1\,med
ium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/u
ploads/2021/07/download.jpg\;214\;236\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2993@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; https://ibiis.sta
nford.edu/events/retreat/2021Hybrid.html
DESCRIPTION:
Keynote:
\n
Self-Supervision for Learning from the Bot
tom Up
\n
Why do self-supervised learning? A common answer is: “beca
use data labeling is expensive.” In this talk\, I will argue that there ar
e other\, perhaps more fundamental reasons for working on self-supervision
. First\, it should allow us to get away from the tyranny of top-down sema
ntic 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 in
triguingly\, there is hope that it might be possible to force a self-super
vised task curriculum to emerge from first principles\, even in the absenc
e 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 it
s course\, research in self-supervised learning is only just beginning.
DTSTART;TZID=America/Los_Angeles:20210927T130000
DTEND;TZID=America/Los_Angeles:20210927T163000
LOCATION:https://ibiis.stanford.edu/events/retreat/2021Hybrid.html
SEQUENCE:0
SUMMARY:2021 IBIIS & AIMI Virtual Retreat
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/2021-ibi
is-aimi-virtual-retreat/
X-COST-TYPE:free
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2903@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:CME\,CME Radiology Grand Rounds\,Radiology
CONTACT:Tricia Hatcliff\; 650-498-7359\; thatcliff@stanford.edu
DESCRIPTION:
CME Grand Rounds – “Community Based Partnered Research: Revisiting a Cri
tical Concept for Radiology”
\n
\n
Christoph L. Lee\,
MD\, MS\, MBA
\nProfessor
\nRadiology
\nUniversity
of Washington
\n
\n
Join from PC\, Mac\, Linux\, iOS or Andro
id: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U
0RmNtUDVWdz09
\nMeeting ID: 600 003 703
\nPassword: 566048\nOr iPhone one-tap (US Toll): +18333021536\,\,600003703# or +16507249
799\,\,600003703#
\nOr Telephone:
\nDial: +1 650 724 9799 (US\,
Canada\, Caribbean Toll) or +1 833 302 1536 (US\, Canada\, Caribbean Toll
Free)
\nInternational numbers available: https://stanford.zoom.us/u/acuqphnvqT
\n
\n
ABSTRACT
\nComing soon!
\n
\n
BIO
\nComing soon!
DTSTART;TZID=America/Los_Angeles:20211008T120000
DTEND;TZID=America/Los_Angeles:20211008T130000
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:CME Grand Rounds – Christoph L. Lee\, MD\, MS\, MBA
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cme-gran
d-rounds-christoph-l-lee-md-ms-mba/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/C-Lee2017_2-214x300-150x150.jpg\;150\;
150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/w
p-content/uploads/2021/07/C-Lee2017_2-214x300-214x300.jpg\;214\;300\;1
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2295@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:Canary Center\,Early Cancer Detection Seminar Ser
ies
CONTACT:Ashley Williams\; ashleylw@stanford.edu\; https://canarycenter.stan
ford.edu/seminars.html
DESCRIPTION:
CEDSS: T
he First Cell: A new model for cancer research and treatment
\n
Azra Raza\, M.D
.
\nChan Soon-Shiong Professor of Medicine
\nDirect
or\, Myelodysplastic Syndrome Center
\nColumbia University Medical Ce
nter
\n
\n
Location: Zoom
\n
Meeting URL: https://stanford.zoom.us/s/99340345860
\nDia
l: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
\nMeeting ID:
993 4034 5860
\nPasscode: 711508
\n
RS
VP Here
\n
\n
ABSTRACT
\n
C
ancer research continues to be predicated on a 1970’s model of research an
d treatment. Despite half a century of intense research\, we are failing s
pectacularly to improve the outcome for patients with advanced disease. Th
ose who are cured continue to be treated mostly with the older strategies
(surgery-chemo-radiation). Our contention is that the real solution to the
cancer problem is to diagnose cancer early\, at the stage of The First Ce
ll. The rapidly evolving technologies are doing much in this area but need
to be expanded. We study a pre-leukemic condition called myelodysplastic
syndrome (MDS) with the hope that we can detect the first leukemia cells a
s the disease transforms to acute myeloid leukemia (AML). Towards this end
\, we have collected blood and bone marrow samples on MDS and AML patients
since 1984. Today\, our Tissue Repository has more than 60\,000 samples.
We propose novel methods to identify surrogate markers that can identify t
he First Cell through studying the serial samples of patients who evolve f
rom MDS to AML.
\n
\n
ABOUT
\n
Dr. Raza
is a Professor of Medicine and Director of the MDS Center at Columbia Univ
ersity in New York\, NY.She started her research in Myelodisplastic Syndro
mes (MDS) in 1982 and moved to Rush University\, Chicago\, Illinois in 199
2\, where she was the Charles Arthur Weaver Professor in Oncology and Dire
ctor\, Division of Myeloid Diseases. The MDS Program\, along with a Tissue
Repository containing more than 50\,000 samples from MDS and acute leukem
ia patients was successfully relocated to the University of Massachusetts
in 2004 and to Columbia University in 2010.
\n
Before moving to New Y
ork\, Dr. Raza was the Chief of Hematology Oncology and the Gladys Smith M
artin Professor of Oncology at the University of Massachussetts in Worcest
er. She has published the results of her laboratory research and clinical
trials in prestigious\, peer reviewed journals such as The New England Jou
rnal of Medicine\, Nature\, Blood\, Cancer\, Cancer Research\, British Jou
rnal of Hematology\, Leukemia\, and Leukemia Research. Dr. Raza serves on
numerous national and international panels as a reviewer\, consultant and
advisor and is the recipient of a number of awards.
\n
\n
Hosted by: Utkan Demirci\, Ph.D.
\nSponsor
ed by: The Canary Center & the Department of Radiology <
/em>
\nStanford University – School of Medicine
DTSTART;TZID=America/Los_Angeles:20211012T110000
DTEND;TZID=America/Los_Angeles:20211012T120000
LOCATION:Venue coming soon!
SEQUENCE:0
SUMMARY:Cancer Early Detection Seminar Series – Azra Raza\, MD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cancer-e
arly-detection-seminar-series-azra-raza-md/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/A_Raza-150x150.png\;150\;150\;1\,mediu
m\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/upl
oads/2019/10/A_Raza-300x200.png\;300\;200\;1\,large\;http://web.stanford.e
du/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/A_Raza.png\
;640\;426\;\,full\;http://web.stanford.edu/group/radweb/cgi-bin/radcalenda
r/wp-content/uploads/2019/10/A_Raza.png\;700\;466\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3007@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:SMAC
CONTACT:https://stanford.zoom.us/webinar/register/WN_nZRvc749QEaQ81621sHHTw
DESCRIPTION:
Alone in the Rin
g (a research-based theatre production about inclusive healthcare
workplaces) is coming to campus during the Annual Stanford School of Medic
ine Diversity Week and National Disability Employment Awareness Month\, SM
AC and Stanford
Medicine and the Muse hope to continue the discussion on how to spark
and sustain change towards inclusive workspaces. Alone in the Ring
is followed by a discussion between the team and audience members. During
the presentation\, audience members are encouraged to reflect: How inclus
ive is your workspace? How could you make it more accessible?
\n
Register for this event
DTSTART;TZID=America/Los_Angeles:20211014T173000
DTEND;TZID=America/Los_Angeles:20211014T190000
SEQUENCE:0
SUMMARY:Alone in the Ring – presented by SMAC and Stanford Medicine and the
Muse
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ndeam/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/09/Screen-Shot-2021-09-16-at-11.12.58-AM-
150x150.png\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi
-bin/radcalendar/wp-content/uploads/2021/09/Screen-Shot-2021-09-16-at-11.1
2.58-AM-300x193.png\;300\;193\;1\,large\;http://web.stanford.edu/group/rad
web/cgi-bin/radcalendar/wp-content/uploads/2021/09/Screen-Shot-2021-09-16-
at-11.12.58-AM-1024x659.png\;640\;412\;1\,full\;http://web.stanford.edu/gr
oup/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/09/Screen-Shot-2021
-09-16-at-11.12.58-AM-e1631805255452.png\;200\;129\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2913@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:CME\,CME Radiology Grand Rounds\,Radiology
CONTACT:Tricia Hatcliff\; 650-498-7359\; thatcliff@stanford.edu
DESCRIPTION:
CME Grand Rounds –
Topic: TBD
\n
Jocelyn D. Chertoff\, MD\, MS
\n
Professor
\nRadiology\, Obstetrics & Gynecology
\nChair\, Radiol
ogy
\nDartmouth Hitchcock Medical Center
\n
\n
Join from
PC\, Mac\, Linux\, iOS or Android: https://stanford.zoom.us/j/60
0003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
\nMeeting ID: 600 00
3 703
\nPassword: 566048
\nOr iPhone one-tap (US Toll): +1833302
1536\,\,600003703# or +16507249799\,\,600003703#
\nOr Telephone:
\nDial: +1 650 724 9799 (US\, Canada\, Caribbean Toll) or +1 833 302 1536
(US\, Canada\, Caribbean Toll Free)
\nInternational numbers availabl
e: https://stanford.zoom.u
s/u/acuqphnvqT
\n
\n
ABSTRACT
\nComi
ng soon!
\n
\n
BIO
\nComing soon!
DTSTART;TZID=America/Los_Angeles:20211022T120000
DTEND;TZID=America/Los_Angeles:20211022T130000
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:CME Grand Rounds – Jocelyn D. Chertoff\, MD\, MS
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cme-gran
d-rounds-jocelyn-d-chertoff-md-ms/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/Chertoff-150x150.jpg\;150\;150\;1\,med
ium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/u
ploads/2021/07/Chertoff.jpg\;196\;257\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3015@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:SMAC
CONTACT:https://med.stanford.edu/facultydiversity/faculty-community/network
s/heal-network.html
DESCRIPTION:
\n
Office of Faculty De
velopment and Diversity and SMAC.
\n
The OFDD team welcomes all S
tanford community members to join our inaugural Health Equity Action Leadership (HE
AL Network) event\, Health Equity Research in the Latinx Community\, w
here faculty who do this work will share their experiences in a fireside c
hat panel.
\n
Moderator: Lisa Goldman-Rosas
\n
Speakers: Dr. Ken
Sutha\, Dr. Peter Poullos\, Dr. Holly Tabor
\n
DTSTART;TZID=America/Los_Angeles:20211026T120000
DTEND;TZID=America/Los_Angeles:20211026T130000
SEQUENCE:0
SUMMARY:Health Equity Action Leadership (HEAL Network) Fireside Chat
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/health-e
quity-action-leadership-heal-network-fireside-chat/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/09/Screen-Shot-2021-09-16-at-11.21.47-AM-
150x150.png\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi
-bin/radcalendar/wp-content/uploads/2021/09/Screen-Shot-2021-09-16-at-11.2
1.47-AM-300x191.png\;300\;191\;1\,large\;http://web.stanford.edu/group/rad
web/cgi-bin/radcalendar/wp-content/uploads/2021/09/Screen-Shot-2021-09-16-
at-11.21.47-AM.png\;596\;379\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2521@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:MIPS\,MIPS Seminar
CONTACT:Ashley Williams\; ashleylw@stanford.edu\; https://med.stanford.edu/
mips/events.html
DESCRIPTION:
MIPS Seminar Series: Title TBA
\n
Steven Paul Poplack\, MD
\nProfessor of Radiology (Breast Imaging)
\nStanford University Med
ical Center
\n
\n
Location: Coming soon!
\n
12:00pm – 12:
45pm Seminar & Discussion
\nRSVP: Coming soon!
\n
\n
ABSTRACT
\n
Coming soon!
\n
\n
ABOUT
\nComing soon!
\n
\n
Hosted by: Katherine F
errara\, PhD
\nSponsored by: Molecular Imaging Program at St
anford & the Department of Radiology
DTSTART;TZID=America/Los_Angeles:20211028T120000
DTEND;TZID=America/Los_Angeles:20211028T124500
LOCATION:Venue coming soon!
SEQUENCE:0
SUMMARY:MIPS Seminar – Steven Paul Poplack\, MD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/mips-sem
inar-steven-paul-poplack-md/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/steven-poplack-150x150.jpg\;150\;150\;
1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-con
tent/uploads/2019/10/steven-poplack-300x300.jpg\;300\;300\;1\,large\;http:
//web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/201
9/10/steven-poplack.jpg\;320\;320\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2937@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:CME\,CME Radiology Grand Rounds\,Radiology
CONTACT:Tricia Hatcliff\; 650-498-7359\; thatcliff@stanford.edu
DESCRIPTION:
CME Grand Rounds
Etta K. Moskowitz Lectureship – Topic: TBD
\n
Elizabeth Krupi
nski\, PhD
\nProfessor & Vice Chair for Research
\nRadi
ology & Imaging Sciences
\nEmory University School of Medicine
\n<
p> \n
Join from PC\, Mac\, Linux\, iOS or Android: https:/
/stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
\nMeeting ID: 600 003 703
\nPassword: 566048
\nOr iPhone one-t
ap (US Toll): +18333021536\,\,600003703# or +16507249799\,\,600003703#
\nOr Telephone:
\nDial: +1 650 724 9799 (US\, Canada\, Caribbean To
ll) or +1 833 302 1536 (US\, Canada\, Caribbean Toll Free)
\nInternat
ional numbers available: h
ttps://stanford.zoom.us/u/acuqphnvqT
\n
\n
ABSTRAC
T
\nComing soon!
\n
\n
BIO
\nComing soon!
DTSTART;TZID=America/Los_Angeles:20211104T173000
DTEND;TZID=America/Los_Angeles:20211104T183000
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:CME Grand Rounds Etta K. Moskowitz Lectureship – Elizabeth Krupinsk
i\, PhD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cme-gran
d-rounds-etta-k-moskowitz-lectureship-elizabeth-krupinski-phd/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/Krupinski.jpg\;144\;144\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2957@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:CME\,CME Radiology Grand Rounds\,Radiology
CONTACT:Tricia Hatcliff\; 650-498-7359\; thatcliff@stanford.edu
DESCRIPTION:
CME Grand Rounds – “Promote Your Academic Career Using Social Me
dia”
\n
Michael Gisondi\, MD
\nAssociate Profes
sor & Vice Chair of Education
\nEmergency Medicine
\nStanford Un
iversity
\n
\n
Join from PC\, Mac\, Linux\, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtU
DVWdz09
\nMeeting ID: 600 003 703
\nPassword: 566048
\n
Or iPhone one-tap (US Toll): +18333021536\,\,600003703# or +16507249799\,\
,600003703#
\nOr Telephone:
\nDial: +1 650 724 9799 (US\, Canada
\, Caribbean Toll) or +1 833 302 1536 (US\, Canada\, Caribbean Toll Free)<
br />\nInternational numbers available: https://stanford.zoom.us/u/acuqphnvqT
\n
\n
ABSTRACT
\nComing soon!
\n
\n
BI
O
\nComing soon!
DTSTART;TZID=America/Los_Angeles:20211112T120000
DTEND;TZID=America/Los_Angeles:20211112T130000
LOCATION:Zoom - See Description for Zoom Link
SEQUENCE:0
SUMMARY:CME Grand Rounds – Michael Gisondi\, MD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/cme-gran
d-rounds-michael-gisondi-md/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/07/michael-gisondi_profilephoto-150x150.j
pg\;150\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radc
alendar/wp-content/uploads/2021/07/michael-gisondi_profilephoto-300x300.jp
g\;300\;300\;1\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcal
endar/wp-content/uploads/2021/07/michael-gisondi_profilephoto.jpg\;350\;35
0\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3033@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; http://ibiis.stan
ford.edu/events/seminars/2021seminars.html
DESCRIPTION:
\n
Saeed Hassanpour\, PhD
\nAssociate
Professor of Biomedical Data Science
\nAssociate Professor of Epidem
iology
\nAssociate Professor of Computer Science
\nDartmouth Gei
sel School of Medicine
\n
Deep Learning for Histology Images
Analysis
\n
Abstract:
\nWith the recen
t expansions of whole-slide digital scanning\, archiving\, and high-throug
hput tissue banks\, the field of digital pathology is primed to benefit si
gnificantly from deep learning technology. This talk will cover several ap
plications of deep learning for characterizing histopathological patterns
on high-resolution microscopy images for cancerous and precancerous lesion
s. Furthermore\, the current challenges for building deep learning models
for pathology image analysis will be discussed and new methodological adva
nces to address these bottlenecks will be presented.
\n
About
:
\n
Dr. Saeed Hassanpour is an Associate Professor in the D
epartments of Biomedical Data Science\, Computer Science\, and Epidemiolog
y at Dartmouth College. His research is focused on machine learning and mu
ltimodal data analysis for precision health. Dr. Hassanpour has led multip
le NIH-funded research projects\, which resulted in novel machine learning
and deep learning models for medical image analysis and clinical text min
ing to improve diagnosis\, prognosis\, and personalized therapies. Before
joining Dartmouth\, he worked as a Research Engineer at Microsoft. Dr. Has
sanpour received his Ph.D. in Electrical Engineering with a minor in Biome
dical Informatics from Stanford University and completed his postdoctoral
training at Stanford Center for Artificial Intelligence in Medicine & Imag
ing.
DTSTART;TZID=America/Los_Angeles:20211117T120000
DTEND;TZID=America/Los_Angeles:20211117T130000
LOCATION:Zoom: https://stanford.zoom.us/j/91788140120?pwd=K2NvMHZ2SUFVWjc1d
2xJUndjTG9lQT09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Deep Learning for Histology Images Analysis
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-deep-learning-for-histology-images-analysis/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/11/Saeed.jpg\;300\;300\,medium\;http://we
b.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/11
/Saeed.jpg\;300\;300\,large\;http://web.stanford.edu/group/radweb/cgi-bin/
radcalendar/wp-content/uploads/2021/11/Saeed.jpg\;300\;300\,full\;http://w
eb.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/1
1/Saeed.jpg\;300\;300
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-2547@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:MIPS\,MIPS Seminar
CONTACT:Ashley Williams\; ashleylw@stanford.edu\; https://med.stanford.edu/
mips/events.html
DESCRIPTION:
MIPS Seminar Series: Title TBA
\n
Matthew Bogyo\, PhD
\nProf
essor of Pathology and of Microbiology and Immunology and\, by courtesy\,
of Chemical and Systems Biology
\nStanford University
\n
\n
Location: Coming soon!
\n
12:00pm – 12:45pm Seminar & Discussion\nRSVP: Coming soon!
\n
\n
ABSTRACT
\n
Coming soon!
\n
\n
ABOUT
\nDr. Bogyo
received a B.Sc. degree in Chemistry from Bates College in 1993 and a Ph.D
. in Biochemistry from the Massachusetts Institute of Technology in 1997.
After completion of his degree he was appointed as a Faculty Fellow in the
Department of Biochemistry and Biophysics at the University of California
\, San Francisco. Dr. Bogyo served as the Head of Chemical Proteomics at C
elera Genomics from 2001 to 2003 while maintaining an Adjunct Faculty appo
intment at UCSF. In the Summer of 2003 Dr. Bogyo joined the Department of
Pathology at Stanford Medical School and was appointed as a faculty member
in the Department of Microbiology and Immunology in 2004. His interests a
re focused on the use of chemistry to study the role of proteases in human
disease. In particular his laboratory is currently working on understandi
ng the role of cysteine proteases in tumorgenesis and also in the life cyc
le of human parasites and bacterial pathogens. Dr. Bogyo currently serves
on the Editorial Board of Biochemical Journal\, Cell Chemical Biology\, Mo
lecular and Cellular Proteomics and is an Academic Editor at PLoS One. Dr.
Bogyo is a consultant for several biotechnology and pharmaceutical compan
ies in the Bay Area and is a founder and board member of Akrotome Imaging
and Facile Therapeutics.
\n
\n
Hosted by: Katherine Ferrar
a\, PhD
\nSponsored by: Molecular Imaging Program at Stanfor
d & the Department of Radiology
DTSTART;TZID=America/Los_Angeles:20211118T120000
DTEND;TZID=America/Los_Angeles:20211118T124500
LOCATION:Venue coming soon!
SEQUENCE:0
SUMMARY:MIPS Seminar – Matthew Bogyo\, PhD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/mips-sem
inar-matthew-bogyo-phd/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2019/10/BogyoHeadshotJuly2017-150x150.jpg\;150
\;150\;1\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar
/wp-content/uploads/2019/10/BogyoHeadshotJuly2017-244x300.jpg\;244\;300\;1
\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-conte
nt/uploads/2019/10/BogyoHeadshotJuly2017.jpg\;320\;393\;
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3039@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; http://ibiis.stan
ford.edu/events/seminars/2021seminars.html
DESCRIPTION:
\n
Indrani Bhattacharya\, PhD
\nPostdoctoral Research Fellow
\nDepartment of Radiology
\nStanfo
rd University
\n
Title: Multimodal Data Fusion for S
elective Identification of Aggressive and Indolent Prostate Cancer on Magn
etic Resonance Imaging
\n
Abstract: Automated method
s for detecting prostate cancer and distinguishing indolent from aggressiv
e disease on Magnetic Resonance Imaging (MRI) could assist in early diagno
sis and treatment planning. Existing automated methods of prostate cancer
detection mostly rely on ground truth labels with limited accuracy\, ignor
e disease pathology characteristics observed on resected tissue\, and cann
ot selectively identify aggressive (Gleason Pattern≥4) and indolent (Gleas
on Pattern=3) cancers when they co-exist in mixed lesions. This talk will
cover multimodal and multi-scale fusion approaches to integrate radiology
images\, pathology images\, and clinical domain knowledge about prostate c
ancer distribution to selectively identify and localize aggressive and ind
olent cancers on prostate MRI.
\n
\n
Rogier van der Sluijs\, PhD
\nPostd
octoral Research Fellow
\nDepartment of Radiology
\nStanford Uni
versity
\n
Title: Pretraining Neural Networks for Me
dical AI
\n
Abstract: Transfer learning has quickly
become standard practice for deep learning on medical images. Typically\,
practitioners repurpose existing neural networks and their corresponding w
eights to bootstrap model development. This talk will cover several method
s to pretrain neural networks for medical tasks. The current challenges fo
r pretraining neural networks in Radiology will be discussed and recent ad
vancements that address these bottlenecks will be highlighted.
DTSTART;TZID=America/Los_Angeles:20211215T120000
DTEND;TZID=America/Los_Angeles:20211215T130000
LOCATION:Zoom: https://stanford.zoom.us/j/95371438521?pwd=Y3BheHpUanpESnh6V
UkycVhlUWtodz09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Indrani Bhattacharya\, PhD & Rogier van der S
luijs\, PhD
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-indrani-bhattacharya-phd-rogier-van-der-sluijs-phd/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2021/12/Indrani.jpg\;200\;200\,medium\;http://
web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2021/
12/Indrani.jpg\;200\;200\,large\;http://web.stanford.edu/group/radweb/cgi-
bin/radcalendar/wp-content/uploads/2021/12/Indrani.jpg\;200\;200\,full\;ht
tp://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/
2021/12/Indrani.jpg\;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3047@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; https://ibiis.sta
nford.edu/events/seminars/2022seminars.html
DESCRIPTION:
\n
Nina Kottler\, MD
\, MS
\nAssociate Chief Medical Officer\, Clinical AI
\nVP C
linical Operations
\nRadiology Partners
\n
Abstract:
\nWe have a call to action in healthcare – we need to drive val
ue. Artificial intelligence (AI)\, if deployed correctly\, can help accom
plish this lofty mission. In this discussion we will review the following
lessons learned in deploying radiology AI at scale: 4 unexpected benefit
s of implementing AI emergent finding triage\; the importance of investing
in AI radiologist education\; how “most” AI needs to be incorporated into
the radiologist workflow\; why a platform is required to deploy AI at sca
le and what a modern platform looks like\; how to use AI to add value to y
our data\; and\, as Dr. Curt Langlotz famously said\, why rads (practices)
who use AI will replace those who don’t (a depiction of what the role of
the radiologist might look like in a tech enabled future).
\n
Bio:
\nDr. Kottler has been a practicing radiologist specia
lizing in emergency imaging for over 16 years. Combining her clinical exp
erience with a graduate degree in applied mathematics\, she has been using
technological innovation to drive value in radiology. As the first radio
logist to join Radiology Partners\, Dr. Kottler has held multiple leadersh
ip positions within her practice and is currently the associate Chief Medi
cal Officer for Clinical AI. Externally Dr. Kottler serves on multiple co
mmittees for the ACR\, RSNA\, and SIIM. Dr. Kottler is also passionate ab
out promoting diversity and creating a culture of belonging. As such she
is a member of the AAWR\, is a member of the diversity and inclusion commi
ttee at SIIM\, serves on the steering committee for RAD=\, and leads the e
ducation and development division of the Belonging Committee within Radiol
ogy Partners.
DTSTART;TZID=America/Los_Angeles:20220119T120000
DTEND;TZID=America/Los_Angeles:20220119T130000
LOCATION:Zoom: https://stanford.zoom.us/j/92632628279?pwd=S3RFdXdEUmEweTNKe
lhrcmVxQUExdz09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: AI In Clinical Use – Lessons Learned
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-ai-in-clinical-use-lessons-learned/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2022/01/Nina-Kottler-2021.jpg\;200\;200\,mediu
m\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/upl
oads/2022/01/Nina-Kottler-2021.jpg\;200\;200\,large\;http://web.stanford.e
du/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2022/01/Nina-Kottle
r-2021.jpg\;200\;200\,full\;http://web.stanford.edu/group/radweb/cgi-bin/r
adcalendar/wp-content/uploads/2022/01/Nina-Kottler-2021.jpg\;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3053@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; https://ibiis.sta
nford.edu/events/seminars/2022seminars.html
DESCRIPTION:
\n
Spyridon (Spyros) Bakas\,
PhD
\nAssistant Professor in the Department of Pathology\,
\nLaboratory Medicine\, and of Radiology
\nCenter for Biomedical Imag
e Computing and Analytics (CBICA)
\nPerelman School of Medicine
\nUniversity of Pennsylvania
\n
Title: Imaging Analytics for N
euro-Oncology:
\nTowards Computational Diagnostics
\n
Ab
stract: Central nervous system (CNS) tumors come with vastly hete
rogeneous histologic\, molecular\, and radiographic landscapes\, rendering
their precise characterization challenging. The rapidly growing fields of
biophysical modeling and radiomics have shown promise in better character
izing the molecular\, spatial\, and temporal heterogeneity of tumors. Inte
grative analysis of CNS tumors\, including clinically acquired multi-param
etric magnetic resonance imaging (mpMRI)\, assists in identifying macrosco
pic quantifiable tumor patterns of invasion and proliferation\, potentiall
y leading to improved (a) detection/segmentation of tumor subregions and (
b) computer-aided diagnostic/prognostic/predictive modeling. This talk wil
l touch upon example studies on this space\, as well as an overview of the
largest to-date real-world federated learning study to detect brain tumor
boundaries.
DTSTART;TZID=America/Los_Angeles:20220216T120000
DTEND;TZID=America/Los_Angeles:20220216T130000
LOCATION:ZOOM: https://stanford.zoom.us/j/98789338790?pwd=OXRORjhYUUdaRGJpU
HJZdzZ5NGw5dz09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Imaging Analytics for Neuro-Oncology: Towards
Computational Diagnostics
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-imaging-analytics-for-neuro-oncology-towards-computational-diag
nostics/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-A
M.jpg\;200\;200\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radc
alendar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-AM
.jpg\;200\;200\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcal
endar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-AM.j
pg\;200\;200\,full\;http://web.stanford.edu/group/radweb/cgi-bin/radcalend
ar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-AM.jpg\
;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3061@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; https://ibiis.sta
nford.edu/events/seminars/2022seminars.html
DESCRIPTION:
\n
Harini Veeraraghavan\, PhD
\nAssociat
e Attending Computer Scientist
\nDepartment of Medical Physics
\nMemorial Sloan-Kettering Cancer Center
\n
Using AI for Long
itudinal Tumor Response Monitoring and AI Guided Cancer Treatments: From L
ab to Clinic
\n
Abstract:
\nCancer pat
ients are imaged with multiple imaging modalities as part of routine cance
r care. However\, the rich information available from the images are not f
ully exploited to better manage patient care through earlier intervention
as well as more precise targeted treatments. In this talk\, I will present
some of the new AI methodologies we have been developing to track tumor r
esponse as well as from routinely acquired imaging applied to image-guided
radiation treatments using CT/cone-beam CT as well as MRI-guided precisio
n treatments. I will also present some demonstration studies of how AI bas
ed automated segmentation and tumor as well as healthy tissue change asses
sment can be used to early detect treatment toxicities to enable clinician
s to better manage cancer care. Finally\, I will show how these developed
methods have been put to routine clinical care for automating radiotherapy
treatment planning at MSK.
DTSTART;TZID=America/Los_Angeles:20220316T120000
DTEND;TZID=America/Los_Angeles:20220316T130000
LOCATION:ZOOM: https://stanford.zoom.us/j/99319571697?pwd=c2lhRkN4cXEzTzFzM
UhKaTVJMHZLQT09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Using AI for Longitudinal Tumor Response Moni
toring and AI Guided Cancer Treatments: From Lab to Clinic
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-using-ai-for-longitudinal-tumor-response-monitoring-and-ai-guid
ed-cancer-treatments-from-lab-to-clinic/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2022/03/harini-veeraraghavan_15_1200x800.jpg\;
200\;200\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar
/wp-content/uploads/2022/03/harini-veeraraghavan_15_1200x800.jpg\;200\;200
\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-conte
nt/uploads/2022/03/harini-veeraraghavan_15_1200x800.jpg\;200\;200\,full\;h
ttp://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads
/2022/03/harini-veeraraghavan_15_1200x800.jpg\;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3071@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; rtotah@stanford.edu\; https://ibiis.stanford.edu/even
ts/seminars/2022seminars.html
DESCRIPTION:
\n
Spyridon (Spyros) Bakas\,
PhD
\nAssistant Professor in the Department of Pathology\,
\nLaboratory Medicine\, and of Radiology
\nCenter for Biomedical Imag
e Computing and Analytics (CBICA)
\nPerelman School of Medicine
\nUniversity of Pennsylvania
\n
Title: Imaging Analytics for N
euro-Oncology: Towards Computational Diagnostics
\n
Central nervous s
ystem (CNS) tumors come with vastly heterogeneous histologic\, molecular\,
and radiographic landscapes\, rendering their precise characterization ch
allenging. The rapidly growing fields of biophysical modeling and radiomic
s have shown promise in better characterizing the molecular\, spatial\, an
d temporal heterogeneity of tumors. Integrative analysis of CNS tumors\, i
ncluding clinically acquired multi-parametric magnetic resonance imaging (
mpMRI)\, assists in identifying macroscopic quantifiable tumor patterns of
invasion and proliferation\, potentially leading to improved (a) detectio
n/segmentation of tumor subregions and (b) computer-aided diagnostic/progn
ostic/predictive modeling. This talk will touch upon example studies on th
is space\, as well as an overview of the largest to-date real-world federa
ted learning study to detect brain tumor boundaries.
DTSTART;TZID=America/Los_Angeles:20220414T110000
DTEND;TZID=America/Los_Angeles:20220414T120000
LOCATION:Zoom: https://stanford.zoom.us/j/98789338790?pwd=OXRORjhYUUdaRGJpU
HJZdzZ5NGw5dz09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Imaging Analytics for Neuro-Oncology: Towards
Computational Diagnostics
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-imaging-analytics-for-neuro-oncology-towards-computational-diag
nostics-2/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-A
M.jpg\;200\;200\,medium\;http://web.stanford.edu/group/radweb/cgi-bin/radc
alendar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-AM
.jpg\;200\;200\,large\;http://web.stanford.edu/group/radweb/cgi-bin/radcal
endar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-AM.j
pg\;200\;200\,full\;http://web.stanford.edu/group/radweb/cgi-bin/radcalend
ar/wp-content/uploads/2022/02/bakas-aibil-headshot-160-215-8.37.55-AM.jpg\
;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3069@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:
DESCRIPTION:
\n
Daniel Marcus\, PhD
\nProfessor of Radiology
\nDirector of the Neuroinformatics Research
Group
\nDirector of the Neuroimaging Informatics and Analysis Center<
br />\nWashington University
\n
Abstract:
\nDeveloping and deplo
ying computational tools for neuro-oncology applications includes a sequen
ce of complex steps to identify appropriate images\, assess image quality\
, annotate\, process and other prepare and manipulate data for analysis. W
e have implemented services and tools on the open source XNAT informatics
platform to automate much of this workflow to improve both its efficiency
and effectiveness. Dr. Marcus will discuss this automated workflow and its
implementation in a number of data sets and applications at Washington Un
iversity.
DTSTART;TZID=America/Los_Angeles:20220420T120000
DTEND;TZID=America/Los_Angeles:20220420T130000
LOCATION:Zoom: https://stanford.zoom.us/j/94439662481?pwd=N1BUc2FqWUt4QVlQM
nNSS21rcEV4UT09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Automated Workflows for Neuro-Oncology Image
Analysis
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-automated-workflows-for-neuro-oncology-image-analysis/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2022/04/Daniel-Marcus.jpg\;200\;200\,medium\;h
ttp://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads
/2022/04/Daniel-Marcus.jpg\;200\;200\,large\;http://web.stanford.edu/group
/radweb/cgi-bin/radcalendar/wp-content/uploads/2022/04/Daniel-Marcus.jpg\;
200\;200\,full\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/w
p-content/uploads/2022/04/Daniel-Marcus.jpg\;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3077@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; rtotah@stanford.edu\; https://ibiis.stanford.edu/even
ts/seminars/2022seminars.html
DESCRIPTION:
\n
\n
\n
\n
Lena Maier-Hein\, PhD
\nHead of Department\, Computer As
sisted Medical Interventions
\nManaging Director\, Data Science and D
igital Oncology
\nManaging Director\, National Center for Tumor Disea
ses
\nGerman Cancer Research Center
\n
Title: Missing the
(Bench)mark?
\n
\n
\n
\n
\n
\n
\n\n
\n
\n
\n
\n
\n
\n
Machine
learning has begun to revolutionize almost all areas of health research. S
uccess stories cover a wide variety of application fields ranging from rad
iology and gastroenterology all the way to mental health. Strikingly\, how
ever\, solutions that perform favorably in research generally do not trans
late well to clinical practice\, and little attention is being given to le
arning from failures. Focusing on biomedical image analysis as a key area
of health-related machine learning\, this talk will present pitfalls\, cav
eats and recommendations related to machine learning-based biomedical imag
e analysis. As a particular highlight\, it will cover yet unpublished work
on two key research questions related to biomedical image analysis compet
itions: 1) How can we best select performance metrics according to the cha
racteristics of the driving biomedical question? And 2) Why is the winner
the best? The results have been compiled based on the input of hundreds of
image analysis researchers worldwide.
\n
\n
\n
\n
\n
\n
\n\n
\n
DTSTART;TZID=America/Los_Angeles:20220518T093000
DTEND;TZID=America/Los_Angeles:20220518T103000
LOCATION:Zoom: https://stanford.zoom.us/j/95872488712?pwd=dDhmT1JPdWtTSlBOQ
1BENmtGOUxjUT09
SEQUENCE:0
SUMMARY:IBIIS & AIMI Seminar: Missing the (Bench)mark?
URL:http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/event/ibiis-ai
mi-seminar-missing-the-benchmark/
X-COST-TYPE:free
X-WP-IMAGES-URL:thumbnail\;http://web.stanford.edu/group/radweb/cgi-bin/rad
calendar/wp-content/uploads/2022/05/Meier-Hein.jpg\;200\;200\,medium\;http
://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/20
22/05/Meier-Hein.jpg\;200\;200\,large\;http://web.stanford.edu/group/radwe
b/cgi-bin/radcalendar/wp-content/uploads/2022/05/Meier-Hein.jpg\;200\;200\
,full\;http://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content
/uploads/2022/05/Meier-Hein.jpg\;200\;200
END:VEVENT
BEGIN:VEVENT
UID:ai1ec-3083@web.stanford.edu/group/radweb/cgi-bin/radcalendar
DTSTAMP:20240329T000314Z
CATEGORIES;LANGUAGE=en-US:AIMI
CONTACT:Ramzi Totah\; 16507214161\; rtotah@stanford.edu\; https://ibiis.sta
nford.edu/events/seminars/2022seminars.html
DESCRIPTION: