The UC San Francisco Preoperative Diffuse #Glioma MRI Dataset doi.org/10.1148/ryai.2… UC San Franciscoimaging UC San Francisco_Ci2 Andreas Rauschecker #AI #ML #MachineLearning

Awesome showcase of the great talents of University of California Health symposium on “AI in Radiology”. No limit to what we can do if we put our heads together. Thanks Albert Hsiao 蕭, MD, PhD for organizing a great meeting.

Great story, great student, great mentor Jae Ho Sohn, MD, MS , and great program UCSF Center for Intelligent Imaging ! “I think of machine learning and AI in medicine as a refined pool of collected wisdom”. Love it!

1/ Hearing about #BERT and wondering why #radiologists are starting to talk more about this Sesame Street character?

Check out this #tweetorial from TEB member Ali Tejani, MD with recommendations to learn more about #NLP for radiology.

UCSF Imaging team trained 3D U-Net for longitudinal assessment of posttreatment diffuse glioma MRIs doi.org/10.1148/ryai.2… Jeff Rudie, MD PhD Andreas Rauschecker Christopher Hess #cancer #AI #MachineLearning

Think Haris Sair et al just put on a masterclass in meeting organization for #ASFNR22 . From crowdsourcing content, to gathering wide ranging experts both new and known, to pre-meeting Q&A for trainees, to his consistent and available presence throughout. Hats off and mahalo.

UCSF Neuroradiology at #ASFNR22 ! ASFNR UCSF Imaging

If I show you a brain MRI of a baby, can you tell me how old the baby is down to a few weeks? No? This computer can. And it learned to look at the pattern of myelination to do so. Yi Li Gunvant Chaudhari Joshua Chen Christopher Hess

Just published Radiology: Artificial Intelligence, we tackle longitudinal assessment of diffuse gliomas, finding that custom longitudinal change networks are as accurate as neuoradiologists.
pubs.rsna.org/doi/10.1148/ry…
UCSF Imaging Andreas Rauschecker Christopher Hess

UCSF Imaging team trained 3D U-Net for longitudinal assessment of posttreatment diffuse glioma MRIs doi.org/10.1148/ryai.2… Jeff Rudie, MD PhD Andreas Rauschecker Christopher Hess #glioma #NeuroRad #MachineLearning

A #DeepLearning model that evaluates myelination patterns can predict the gestationally corrected age of neonates & infants on the basis of T1- and T2-weighted MRI scans of the brain. bit.ly/3be77n6 Great work Andreas Rauschecker Yi Li & team!

Great work by our rising stars Joshua Chen and Gunvant Chaudhari !

Excited to be part of this work showing factors that may impact neurocognition after radiation in pediatric brain tumor survivors. Auto-quantified radiation-related abnormalities -> helpful adjunct to other predictors of cognition. UCSF Imaging UCSF Center for Intelligent Imaging frontiersin.org/articles/10.33…

Great opportunity to join our group for any of you neuroradiologists wanting to move to the wonderful Bay Area!

A warm welcome to our new UCSF ACGME neuroradiology fellows and congratulations to our new Clinical Instructors! We look forward to a great year!

Delighted to see the launch of this program at UC San Francisco, a UCSF Neurosurgery and UC San Franciscoimaging collaboration that once again brings the best of advancements in neuroscience to our patients UC San FranciscoHospitals

Radiology #BERT identifies and corrects speech recognition errors in #radiology reports doi.org/10.1148/ryai.2… Andreas Rauschecker Jae Ho Sohn, MD, MS UCSF Imaging #reporting #AI #ML

Congratulations to this group! We look forward to welcoming you to @UCSFImaging. 👏🎉🥳