Ronald M. Summers
Also known as Ronald Marc Summers
Ronald Summers is a radiologist at the NIH Clinical Center whose lab applies deep learning and computer-aided detection to medical images and releases large public image datasets for training diagnostic AI. After an MD and PhD at the University of Pennsylvania in 1988, a radiology residency at the University of Michigan and an MRI fellowship at Duke, he joined the NIH Clinical Center in 1994 and received the Presidential Early Career Award for Scientists and Engineers in 2000. He was first author of a 2005 Gastroenterology study of computer-aided polyp detection on CT virtual colonoscopy, and his lab released more than 100,000 chest X-ray images in 2017 and the DeepLesion CT dataset in July 2018. In July 2025, he served as a general chair and program chair of the MIDL conference, and he received the NIH Director's Award in 2026. He is a Senior Investigator who directs the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory.
Timeline
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1981–1994
Penn, Michigan and Duke training
He earns a BA in physics at the University of Pennsylvania in 1981 and an MD and PhD in Medicine/Anatomy and Cell Biology there in 1988. He completes a radiology residency at the University of Michigan in Ann Arbor from 1989 to 1993 and an MRI fellowship at Duke University from 1993 to 1994.
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1994
Joining the NIH Clinical Center
In 1994, he joins the Radiology and Imaging Sciences Department at the NIH Clinical Center in Bethesda, Maryland, where he works as a tenured Senior Investigator and Staff Radiologist.
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2000
A presidential early career award
He receives the Presidential Early Career Award for Scientists and Engineers in 2000, presented by Dr. Neal Lane, President Clinton's science advisor.
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2005
Computer-aided virtual colonoscopy
In 2005, he is first author of a Gastroenterology study that tests a computer-aided polyp detection program on CT virtual colonoscopy in 1,186 screening patients at three medical centers. The program's per-patient sensitivity is comparable to that of optical colonoscopy for adenomas of 8 mm or larger.
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2016
Deep networks for computer-aided detection
In February 2016, he is one of nine authors of an arXiv paper on deep convolutional neural networks for computer-aided detection. It compares CNN architectures, dataset scale and transfer learning from ImageNet on lymph node detection and interstitial lung disease classification, and reports 85% sensitivity at 3 false positives per patient for mediastinal lymph nodes.
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2017–2018
Public chest X-ray and CT datasets
In 2017, his lab releases 100,000 anonymized chest X-ray images from 30,000 patients, so that researchers can teach computers to detect and diagnose disease. In July 2018, the lab introduces DeepLesion in the Journal of Medical Imaging, a CT dataset of 32,735 lesions from 4,427 patients, with Summers as senior author. He gives the keynote at the inaugural MIDL conference in 2018.
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2025–2026
MIDL chair and NIH Director's Award
In July 2025, he co-chairs the organizing and program committees of the Medical Imaging with Deep Learning (MIDL) conference, as a general chair and a program chair. In 2026, he receives the NIH Director's Award.
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As of October 2026
Senior Investigator at NIH
He is a Senior Investigator and Staff Radiologist at the NIH Clinical Center, where he directs the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory. He is the former founding Chief of the NIH Clinical Image Processing Service, has co-authored over 700 articles and is a co-inventor on 17 patents.
Career
- Since 1994National Institutes of HealthSenior Investigator and Staff Radiologist
- NowRadiology and Imaging Sciences DepartmentDirector
- 2019–2023University of Wisconsin–Madison
Education
- 1994Duke UniversityMRI Fellow
- 1993University of MichiganRadiology Resident
- 1988University of PennsylvaniaMD and PhD in Medicine/Anatomy and Cell Biology
- 1981University of PennsylvaniaBA in physics
Most-cited works
- Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
- The Medical Segmentation DecathlonWith Bram van Ginneken, Klaus Maier-Hein, Lena Maier-Hein, Olaf Ronneberger and Sebastien Ourselin
- Preparing Medical Imaging Data for Machine Learning
- DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation
- Deep learning in medical imaging and radiation therapyWith Maryellen Lissak Giger
Sources and credits
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- Ronald M. Summers, M.D., Ph.D. | Principal Investigators | NIH Intramural Research Program
- Ronald Summers - Wikipedia
- Computed Tomographic Virtual Colonoscopy Computer-Aided Polyp Detection in a Screening Population
- Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
- Research Briefs | NIH Intramural Research Program
- NIH Clinical Center Releases CT Image Dataset - Health IT - Hospimedica.com
- Organization | MIDL 2025



