Matt Bigelow CNMT, RT(N)(CT)Biomedical Imaging Consultant
Sema Candemir, PhDResearch Scientist
Mutlu Demirer, PhD, MBAResearch Scientist
Engin Dikici, PhDResearch Scientist
Barbaros Selnur Erdal, PhDDirector, Laboratory for Augmented Intelligence in Imaging
Vikash Gupta, PhDResearch Scientist
Kevin Little, PhDAssistant Professor of Radiology and Diagnostic Medical Physicist
Luciano Prevedello, MD, MPHVice Chair, Medical Informatics & Augmented Intelligence in Imaging
Richard D. White, MD, MSChairman, Department of Radiology
Joseph S. Yu, M.D.Professor of Radiology and Orthopedic Surgery
Sarah M. YuResearch Intern
Matt attended The Ohio State University for his Bachelors in Radiologic Sciences and Therapy and is currently a May 2019 MBA candidate at the Fisher School of Business at The Ohio State University.
Matt’s current role in the lab consists of compiling all data (images) for each use case, extracting them from our PACS system, and sorting for labeling and tagging. Matt also helps develop the GUIs used in tagging/labeling our training data.
Dr. Candemir is a research scientist in the Ohio State University Wexner Medical Center. Her research interests are image processing, medical image analysis and computer vision. She was a postdoctoral researcher in Lister Hill National Center for Biomedical Communications in National Library of Medicine, NIH. She was a team member of chest X-ray screening, people locator, and age-related eye disease detection projects. Prior to joining NLM, she worked as a postdoctoral researcher at University of Missouri-Columbia, where she collaborated with Air Force Research Laboratory and Kitware Company towards robust target tracking in wide area imagery.
Awards and Certificates:
- 2017, NLM Honor Award: In Recognition and Appreciation of Exceptional Service by a Contractor, National Library of Medicine.
- 2017, Best Paper Award, 30th IEEE International Symposium on Computer-Based Medical Systems, “Novel Method for Storyboarding Biomedical Videos for Medical Informatics.
- 2016, Team Award, Recognition and Appreciation of Special Achievement, In recognition of a smart phone app to detect malaria – Watch it, Parasite! National Library of Medicine.
- 2014, Certificate and Team Award, HHS – Ignites Pathway Award for the Automatic X-ray Screening for Rural Areas, U.S. Department of Health and Human Services.
- 2014, Certificate of Appreciation: For dedicated effort in curating chest X-ray image dataset, Communication Engineering Branch, National Library of Medicine.
Reviewer – Several peer-reviewed journals including Computer Methods and Programs in Biomedicine , Elsevier, Journal of IEEE Transaction on Biomedical Engineering, and Journal of IEEE Transaction of Medical Imaging.
Technical Program Committee Member: 2018-Int.Conf. on Recent Trends in Image Processing and Pattern Recognition. 2017 – IEEE Life Sciences Conference.
Mutlu received his Ph.D. in 2010 in Electrical and Electronics Engineering from Uludag University in Bursa, Turkey. His research interests include image processing and artificial intelligence.
Engin Dikici, PhD
Dr. Dikici received his Masters of Science degree from the Computer and Information Science Department at the University of Pennsylvania in 2006, and PhD degree in Biomedical Engineering from College of Medicine of Norwegian University of Science and Technology in 2012.
Dr. Dikici’s research interests include segmentation, registration, real time tracking and synthesis of medical images.
Barbaros Selnur Erdal
Dr. Erdal received his PhD in the field of Electrical and Computer Engineering from The Ohio State University and serves as an Assistant Professor of Radiology and Biomedical Informatics. He is the Assistant Chief of Medical Imaging Informatics at the OSU Wexner Medical Center’s Department of Radiology, the Director of Laboratory for Augmented Intelligence in Imaging, and Director of Scholarly Activities.
His primary research interests include:
1) the use of data mining and pattern recognition techniques to support research, operational and educational needs of radiological and clinical systems;
2) image processing and texture analysis;
3) application of machine learning techniques to large scale image datasets. He also serves as the Lead Scientist in many collaborative research and development conducted under Master Research Agreements between the Ohio State University and Siemens Healthineers or NVidia Corporation related to Deep Learning/Machine Learning/Artificial Intelligence in medical imaging in the Department of Radiology.
Throughout his career he has utilized his skills as an engineer and information scientist to build bridges between the medical and engineering domains in order to improve existing systems and assist the next generation of trainees, both in Engineering and Health Sciences, to help build the systems of tomorrow.
Vikash is a research scientist in the Department of Radiology, in the College of Medicine at the Ohio State University.
He was a postdoctoral researcher at Imaging Genetics Center at the University of Southern California between June, 2015 until Feb 2018.
His research interests includes statistical analysis, predictive modeling, clustering algorithms and deep learning
Kevin Little, PhD
Dr. Little is an Assistant Professor of Radiology and Diagnostic Medical Physicist at the Ohio State University Wexner Medical Center. He completed a PhD in Medical Physics in 2014 at the University of Chicago, where he also completed a clinical imaging physics residency in 2016.
He is board certified in diagnostic medical physics by the American Board of Radiology.
Dr. Little is a member of the American Association of Physicists in Medicine (AAPM) Radiography and Fluoroscopy Subcommittee as well as co-chair of the AAPM Task Group on Development of Standards for Vendor-Neutral Reject Analysis in Radiography.
Division Chief, Medical Imaging Informatics
Dr. Prevedello is an Associate Professor of Radiology at the Ohio State University Wexner Medical Center. He is the Division Chief of Medical Imaging Informatics and Medical Director of the 3D and Advanced Visualization Lab.
Following his residency in Radiology, Dr. Prevedello has received formal training in Imaging Informatics, Quality and Safety as well as Diagnostic Radiology with emphasis on Evidence-Based Imaging, Diagnostic Neuroimaging and Emergency Radiology at Brigham and Women’s Hospital – Harvard Medical School.
He obtained his Master’s degree in Public Health at Harvard School of Public Health.
He is Board Certified in Radiology, Neuroradiology and Clinical Informatics.
Dr. Prevedello is part of the Board of Directors of the Society for Imaging Informatics in Medicine. He also chairs the Machine Learning Steering committee at the Radiological Society of North America and serves as an active member in the Radiology Informatics Committee, Structured Reporting Subcommittee and Scientific Program Committee (Radiology Informatics). Dr. Prevedello is an Associate Editor of the upcoming Radiology: Artificial Intelligence Journal. At the American College of Radiology, Dr. Prevedello serves as a member in the Informatics Advisory Council.
Richard D. White, MD, MS
Richard D. White MD, MS
A tenured Professor of Radiology, Dr. White has served as the Chairman of the Department of Radiology at the Ohio State University College of Medicine/Wexner Medical Center since July, 2010, succeeding his chairmanship at the University of Florida College of Medicine at the University of Florida & Shands-Jacksonville (March, 2006-July, 2010).
These appointments followed his serving at the Cleveland Clinic Foundation (1989-2006) as Head, Section of Cardiovascular Imaging, Department of Radiology and Clinical Director, Center for Integrated Non-Invasive Cardiovascular Imaging, representing the interests of Radiology (Departments of Diagnostic Radiology and Molecular & Functional Imaging), Medicine (Department of Cardiovascular Medicine), and Surgery (Department of Thoracic & Cardiovascular Surgery) in cardiovascular imaging.
Dr. White received his medical degree from the Duke University School of Medicine in 1981. Before starting post-graduate training in 1982, he was a Fellow of the Sarnoff Foundation for Cardio-Vascular Research at the Duke University Medical Center. He then completed residency training in Diagnostic Radiology at the University of California-San Francisco; this resulted in Certification by the American Board of Radiology in 1986. He then enrolled in a 2-year NIH fellowship in Cardiovascular Imaging within the Department of Radiology and Cardio-Vascular Research Institute, University of California‑San Francisco. After completion of training, Dr. White held the positions of Director, Cardiovascular MRI at the Georgetown University Hospital (1987‑1988) and Head, Section of Cardiovascular Imaging at the University Hospitals of Cleveland (1988‑1989), before joining the Cleveland Clinic Foundation.
Throughout his career, he has been concerned with the development, initial implementation, and eventual broad-scale clinical application of advanced MR and CT techniques for assessment of cardiovascular diseases. More recently, he has become focused on medical imaging informatics, including machine learning/artificial intelligence, and recently completed a MS Heath Informatics program at Northwestern University in September, 2018.
Joseph S. Yu, M.D.
Joseph S. Yu., M.D., Professor of Radiology and Orthopedic Surgery, currently serves as Vice Chairman of Academic Affairs and Education. He obtained his undergraduate and medical degrees from the Ohio State University. After residency in diagnostic radiology at his alma mater, Dr. Yu completed an Osteoradiology Fellowship at the University of California, San Diego. He has served as Director of the Musculoskeletal Division since 1994.
Dr. Yu is the sole author of the popular Musculoskeletal Imaging: Case Review, in its third edition, and was co-editor of the 2008 ARRS categorical course syllabus State-of-the-Art Emergency and Trauma Radiology. In 2015, he co-edited Problem Solving in Emergency Radiology, which is endorsed by the American Society of Emergency Radiology (ASER).
He is Past President of the ASER, and serves on numerous national and international committees in several distinguished radiology organizations including the American Board of Radiology, and also serves on the American College of Radiology (ACR) Appropriateness Criteria Panel in Musculoskeletal Imaging. He has received honorary fellow status in both the ASER and ACR.
Dr. Yu has been an active participant in funded research including the prestigious multi-year Osteoarthritis Initiative Grants. To date, he has authored 300 papers, chapters, and abstracts, and delivered over 170 national and international lectures. He has recently focused his research interests on applying machine learning to a variety of musculoskeletal conditions, and has numerous projects using Artificial Intelligence in joint imaging.
Sarah M. Yu
Sarah is a research intern in the Department of Radiology. She graduated summa cum laude from the Ohio State University with a Bachelor of Science in Biochemistry. She is currently a medical student in the College of Medicine at the Ohio State University, and has published several research projects in radiology.