Evaluating the Future Role of Surgical AI in the Operating Room

By Adnan Alseidi, MD, MEd on November 15, 2021
In a multicenter study, a team of investigators sought to develop and evaluate the performance of AI models that can identify safe and dangerous zones of dissection, and anatomical landmarks during laparoscopic cholecystectomy (LC), a surgical treatment of gallbladder disease.

AI and Lung Cancer Screening: Using AI to Improve Nodule Detection

By Jae Ho Sohn, MD, MS on November 08, 2021
Dr. Sohn's recent published research involves high precision lung cancer nodule detection. He talks about this research and other topics related to AI and lung cancer screening.

COVID-19 Screening: A Set of Protocols to Validate Deep Learning Algorithms for Chest X-Ray (CXR) Imaging

By Sharmila Majumdar, PhD on November 01, 2021
A recently published paper proposes a set of protocols to validate deep learning algorithms, highlights potential gaps in using neural networks for analyzing these x-rays, including a region of interest Hide-and-Seek protocol, which emphasizes or hides key regions of interest from CXR data.

Automated AI Coronary Artery Calcium Scoring is Live on all UCSF Non-Contrast Chest CTs

By John Mongan, MD, PhD and Kimberly Kallianos, MD on October 20, 2021
A multi-center team (including UCSF) took part in a study and developed a fully automatic, end-to-end deep learning model for automated CAC scoring using routine non-gated unenhanced chest CT exams.

Improving Simultaneous PET/MR through Machine Learning

By Peder Larson, PhD on September 27, 2021
Here at the UCSF Center for Intelligent Imaging (ci2), a team of investigators led by Peder Larson, PhD and Thomas Hope, MD are currently working on improving simultaneous PET/MR systems using machine learning.

UCSF ci2 and DAIR Collaborate to Improve Detection of Clinically Significant Prostate Cancer from Prostate MRI

By Peder Larson, PhD on September 22, 2021
The UCSF Center for Intelligent Imaging (ci2) and the Duke Center for Artificial Intelligence in Radiology (DAIR) are collaborating to improve the detection of clinically significant prostate cancer from prostate MRI.

Meet Abhejit Rajagopal, PhD, UCSF Postdoctoral Scholar

By Abhejit Rajagopal, PhD on September 20, 2021
It's National Postdoc Appreciation Week! Meet Abhejit Rajagopal, PhD, a UCSF postdoctoral scholar who works closely with PIs at the Center for Intelligent Imaging (ci2).

Lessons Learned from Real-World Federated Learning: Experience with COVID-19 Modeling at UCSF

By Jason Crane, PhD and Pablo Damasceno, PhD on September 15, 2021
Researchers at NVIDIA, one of the UCSF ci2's key collaborators, worked with Mass General Brigham on an initiative called EXAM (EMR CXR AI Model) that brought together a large, diverse team of 20 hospitals from around the world to predict COVID-19 outcomes using Machine Learning. UCSF was one of...

An AI Algorithm Accurately Predicts Delayed Radiology Turnaround Times

By Jae Sohn, MD, MS on September 07, 2021
The Big Data in Radiology (BDRAD) research team developed a machine learning model – aided by natural language processing (NLP) components - to predict delayed turnaround time during non-business hours and identify factors that contribute to this delay.

Second Annual Summer Symposium Highlights UCSF ci2 and RIDR Program Interns

By Valentina Pedoia, PhD on August 26, 2021
This month, the UCSF Center for Intelligent Imaging (ci2) and the Department of Radiology and Biomedical Imaging hosted their Second Annual Summer Symposium highlighting the diverse and innovative research that is happening within the center and in the department.