Examining Interinstitutional Portability of a Deep Learning Brain MRI Lesion Segmentation Algorithm

By Andreas Rauschecker, MD, PhD on January 28, 2022
Investigators from UCSF Radiology and Penn Radiology sought to figure out why and also assess the effect of multi-institutional training datasets for mitigating performance loss.

Using Bayesian Deep Learning for more Accurate and Robust PET/MRI Scanning

By Peder Larson, PhD, Thomas Hope, MD and Andrew Leynes on January 24, 2022
Hybrid PET/MRI systems combine the functional information from PET tracers with the soft tissue contrast from MRI. Here at the UCSF Center for Intelligent Imaging (ci2), Peder Larson, PhD and Thomas Hope, MD lead a team of investigators interested in developing improvements for simultaneous PET/MR...

Recent Research Looks at Deep Learning for Alzheimer's Disease

By Lea Grinberg, MD, PhD and Duygu Tosun-Turgut, PhD on January 17, 2022
A team of investigators sought to answer this question: How to fully characterize the binding properties of the tau PET tracers, and to assess their usefulness as an early biomarker of the underlying pathology?

The Future of AI for Diagnosis

By Julia Adler-Milstein, PhD on January 04, 2022
Julia Adler-Milstein, PhD, a member of the UCSF Center for Intelligent Imaging (ci2), was lead author on a viewpoint highlighting the importance of shifting the role of diagnostic AI from predicting labels to "wayfinding," known as interpreting context and providing cues that guide the...

Using Deep Learning and Diffusion-Weighted Imaging to Improve Noninvasive Classification of Glioma

By Janine Lupo, PhD on December 16, 2021
A team of UCSF investigators set out to improve the noninvasive classification of glioma genetic subtypes with deep learning and diffusion-weighted imaging. Their study was recently published in Neuro-Oncology, the journal for the society of Neuro-oncology (SNO).

Precision Psychiatry for Adolescent Depression – A Vision for the Future

By Olga Tymofiyeva, PhD on December 13, 2021
Olga Tymofiyeva, PhD uses MRI in her daily work as a researcher to study the brain, especially those of adolescents.

A Great Showcase of AI at RSNA21!

By UCSF Center for Intelligent Imaging (ci2) team on December 06, 2021
The UCSF Center for Intelligent Imaging (ci2) was proud of our members who presented on a variety of topics, and we were equally delighted to see the extensive AI programming. Here are a few highlights we wanted to share!

UCSF ci2 Investigators Study Osteoarthritis with AI Applied to MRI

By Francesco Calivà, PhD on November 30, 2021
Investigators from the UCSF Center for Intelligent Imaging (ci2) recently reviewed how recent applications of deep learning have improved imaging-based understanding of OA. The work, led by Francesco Calivà, PhD and Nikan Namiri, was recently published in Nature Reviews - Rheumatology.

Using a digital Swarm® platform to improve consensus among radiologists

By Rutwik Shah, MD on November 22, 2021
UCSF Center for Intelligent Imaging (ci2) explored the use of swarm intelligence to address the two problems simultaneously: low consensus among experts and Interpersonal biases seen in teams-based decisions.

UCSF ci2 Investigators Shine at 2021 Imaging Research Symposium

By Valentina Pedoia, PhD on November 18, 2021
Given the important role that artificial intelligence (AI) and deep learning continues to play in radiology and biomedical imaging research, investigators from the UCSF Center for Intelligent Imaging (ci2) had a strong presence at this year's event.