Imaging Informatics electiveOur residents can schedule an elective experience and/or mini-fellowship in Informatics and Artificial Intelligence, to help the resident understand the current and future state of advanced technologies in Radiology.
We believe that research in the field of AI as it relates to Radiology is critical to the future of our specialty, and we strongly encourage residents to become involved in AI research with our Imaging Informatics team. See the articles below for examples of the type of cutting-edge research projects with which our residents can be involved:
Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI
Engin Dikici, John L. Ryu, Mutlu Demirer, Matthew Bigelow, Richard D. White, Wayne Slone, Barbaros Selnur Erdal, Luciano M. Prevedello
Nationwide Trends in Use of Catheter-Directed Therapy for Treatment of Pulmonary Embolism in Medicare Beneficiaries from 2004 to 2016.
Gayou EL, Makary MS, Hughes DR, Hemingway J, Elliott ED, Spain JW, Prevedello LM.
J Vasc Interv Radiol. 2019
Streamlining Communications and Enabling Point-of-care Education in Radiology Through a Mobile Application Solution.
Makary MS, Hartwell C, Egbert NK, Prevedello LM. Curr Probl Diagn Radiol. 2019
Diagnostic Accuracy of Digital Breast Tomosynthesis in the Evaluation of Palpable Breast Abnormalities.
Hawley JR, Kang-Chapman JK, Bonnet SE, Kerger AL, Taylor CR, Erdal BS. Acad Radiol. 2018
Radiology and Enterprise Medical Imaging Extensions (REMIX).
Erdal BS, Prevedello LM, Qian S, Demirer M, Little K, Ryu J, O'Donnell T, White RD.
J Digit Imaging. 2018
Automated Critical Test Findings Identification and Online Notification System Using Artificial Intelligence in Imaging.
Prevedello LM, Erdal BS, Ryu JL, Little KJ, Demirer M, Qian S, White RD.
National Imaging Informatics Course:
The department sponsors all residents to take this week-long course in Imaging Informatics. Through lectures, small group discussions, and problem solving situations, trainees will learn practical concepts and gain knowledge in this evolving field.
We have 24 staff members in Imaging Informatics, and 5 in the AI2 lab (in addition to Radiology faculty). In the lab you will find 16 advanced GPU-enabled systems including a DGX-station and a DGX-1 representing more than 120,000 cores (a CPU in a typical computer which has up to 8 cores) with total 667 GB of GPU memory, more than 1600 GB of system memory and over 100TB of disc storage.
If you would like more information on our efforts in Imaging Informatics and AI, we encourage you to visit our department’s Laboratory for Augmented Intelligence in Imaging website. You can also reach out to Diagnostic Radiology resident, Dr. Angel Hatef, at Angel.Hatef@osumc.edu for any additional information.