Search by Department
Dr. Ronald M. Summers has co-authored over 400 journal, review and conference proceedings articles and is a coinventor on 14 patents.
Dr. Summers received the BA degree in physics and the MD and PhD degrees in Medicine/Anatomy and Cell Biology from the University of Pennsylvania.
He completed a medical internship at the Presbyterian-University of Pennsylvania Hospital, Philadelphia, PA, a radiology residency at the University of Michigan, Ann Arbor, MI, and an MRI fellowship at Duke University, Durham, NC.
In 1994, he joined the Radiology and Imaging Sciences Department at the NIH Clinical Center in Bethesda, MD. where he is now a tenured Senior Investigator and Staff Radiologist. In 2013, he was named a Fellow of the Society of Abdominal Radiologists.
He directs the Imaging Biomarkers and Computer-Aided Diagnosis (CAD) Laboratory and is former and founding Chief of the NIH Clinical Image Processing Service.
In 2000, he received the Presidential Early Career Award for Scientists and Engineers, presented by Dr. Neal Lane, President Clinton’s science advisor. In 2012, he received the NIH Director’s Award, presented by NIH Director Dr. Francis Collins. In 2017, he received the NIH Clinical Center Director’s Award.
His research interests include deep learning, virtual colonoscopy, CAD and development of large radiologic image databases. His clinical areas of specialty are thoracic and abdominal radiology and body cross-sectional imaging.
He is a member of the editorial boards of the Journal of Medical Imaging, Radiology:Artificial Intelligence and Academic Radiology and a past member of the editorial board of Radiology. He is a program committee member of the Computer-aided Diagnosis section of the annual SPIE Medical Imaging conference and was co-chair of the entire conference in 2018 and 2019. He was Program Co-Chair of the 2018 IEEE ISBI symposium.
See his Curriculum Vitae.
Editorials and Review Articles (PubMed link)
Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM, Giger ML. Deep learning in medical imaging and radiation therapy. Med Phys 46(1):e1-e36 (2019) https://doi.org/10.1002/mp.13264.
Summers RM. Deep Learning Lends a Hand to Pediatric Radiology. (Invited Editorial) Radiology 287:323-325 (2018).
Kontos D, Summers RM, Giger M. Special Section Guest Editorial: Radiomics and Deep Learning. Journal of Medical Imaging. 4 (4), 041301 (4 January 2018). doi:10.1117/1.JMI.4.4.041301
Summers RM. Are We at a Crossroads or a Plateau? Radiomics and Machine Learning in Abdominal Oncology Imaging. Abdominal Radiology (2018) https://doi.org/10.1007/s00261-018-1613-1.
Kohli MD, Summers RM, Geis JR. Medical Image Data and Datasets in the Era of Machine Learning—Whitepaper from the 2016 C-MIMI Meeting Dataset Session. J Digit Imaging DOI 10.1007/s10278-017-9976-3 (2017).
Summers RM. Progress in Fully-automated Abdominal CT Interpretation. AJR 207: 67-79 (2016).
Greenspan H, Van Ginneken B, Summers RM. Guest Editorial: Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique. IEEE TMI 35(5) 1153-1159 (2016).
Summers RM. Texture analysis in radiology: Does the emperor have no clothes? (Invited Commentary) Abdominal Imaging (2016). DOI: 10.1007/s00261-016-0950-1
Summers RM. Tumor Response Assessment Using Volumetric Doubling Time: Better than RECIST? Academic Radiology 21:947–949 (2014).
Wang S, Burtt K, Turkbey B, Choyke PL, Summers RM. Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research. BioMed Research International Article ID 789561:1-11 (2014).
Huo Z*, Summers RM*, Paquerault S, Lo J, Hoffmeister J, Armato SG III, Freedman MT, Lin J, Ben Lo S-C, Petrick N, Sahiner B, Fryd D, Yoshida H, Chan H-P. Quality Assurance and Training Procedures for Computer-aided Detection and Diagnosis Systems in Clinical Use. Medical Physics 40(7): 077001-1 to 13 (2013). * These two authors contributed equally to this work.
Petrick N*, Sahiner B*, Armato III SG, Bert A, Correale L, Delsanto S, Freedman MT, Fryd D, Gur D, Hadjiiski L, Huo Z, Jiang Y, Morra L, Paquerault S, Raykar V, Salganicoff M, Samuelson F, Summers RM, Tourassi G, Yoshida H, Zheng B, Zhou C, Chan H-P. Evaluation of Computer-Aided Detection and Diagnosis Systems. Medical Physics 40(8): 087001-1 to 17 (2013).
Summers RM. Evaluation of computer-aided detection devices: consensus is developing. Acad Radiol. 19(4):377-9 (2012).
Wang S, Summers RM. Machine learning and radiology. Med Image Anal. 16(5):933-51 (2012).
Summers RM. Polyp size measurement at CT colonography: What do we know and what do we need to know? Radiology 255(3):707-720 (2010).
Summers RM. Dose Reduction in CT: The Time Is Now. Academic Radiology 17 (10): 1201-1202 (2010).
Summers RM. Roadmaps for Advancement of Radiologic Computer-Aided Detection in the Twenty-First Century. Radiology 229:11-13 (2003).
Journal Articles (PubMed link)
Wang X, Peng Y, Lu L, Lu Z, Summers RM. TIE: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-rays. IEEE CVPR, pp. 9049-9058 (2018).
Yan K, Wang X, Lu L, Zhang L, Harrison A, Bagheri M, Summers RM. Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database. IEEE CVPR, pp. 9261-9270 (2018).
Yan K, Wang X, Lu L, Summers RM. DeepLesion: Automated Mining of Large-Scale Lesion Annotations and Universal Lesion Detection with Deep Learning. Journal of Medical Imaging 5(3), 036501 (2018), doi: 10.1117/1.JMI.5.3.036501.
Wang X, Peng Y, Lu L, Lu Z, Bagheri M, Summers RM. ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases. IEEE CVPR 2017, pp. 2097-2106 (2017) at http://openaccess.thecvf.com/CVPR2017.py, pp. 3462-3471 through IEEE; and https://arxiv.org/abs/1705.02315. https://doi.org/10.1109/CVPR.2017.369.
Burns JE, Yao J, Summers RM. Automated Detection and Classification of Vertebral Body Compression Fractures and Bone Density on CT. Radiology 284(3):788-797 (2017).
Liu J, Wang D, Lu L, Wei Z, Kim L, Turkbey EB, Sahiner B, Petrick N, Summers RM. Detection And Diagnosis Of Colitis On Computed Tomography Using Deep Convolutional Neural Networks. Med Phys 44(9):4630-4642 (2017) doi: 10.1002/mp.12399.
Shin HC, Roberts K, Lu L, Demner-Fushman D, Yao J, Summers RM. Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation. IEEE CVPR, pp. 2497-2506 and arXiv:1603.08486 (2016).
Roth HR, Lu L, Liu J, Yao J, Seff A, Cherry K, Kim L, Summers RM. Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation. IEEE TMI 10.1109/TMI.2015.2482920 35(5):1170-1181 (2016).
Shin H-C, Roth HR, Gao M, Lu L, Xu Z, Nogues I, Yao J, Mollura D, Summers RM. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning. IEEE TMI 10.1109/TMI.2016.2528162 35(5):1285-1298 (2016).
Shin HC, Lu L, Kim L, Seff A, Yao J, Summers RM. Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation. J Machine Learning Research 17(107):1-31 (2016).
Burns JE, Yao J, Munoz H, Summers RM. Automated Detection, Localization, and Classification of Traumatic Vertebral Body Fractures in the Thoracic and Lumbar Spine on Computed Tomography. Radiology 278(1):64-73 (2016), http://dx.doi.org/10.1148/radiol.2015142346 (2015).
Roth HR, Lu L, Seff A, Cherry KM, Hoffman J, Wang S, Liu J, Turkbey E, Summers RM. A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations. In P. Golland et al. (Eds.): MICCAI 2014, Part I, LNCS 8673, pp. 520–527, 2014. Dr. Roth was a finalist for the Young Scientist Publication Impact Award at MICCAI 2017 based on this publication and a winner of the MICCAI 2018 5-year Young Researcher Publication Impact Award.
Liu J, Wang S, Linguraru MG, Yao J, Summers RM. Tumor Sensitive Matching Flow: A Variational Method to Detecting and Segmenting Perihepatic and Perisplenic Ovarian Cancer Metastases on Contrast-Enhanced Abdominal CT. Medical Image Analysis 18:725-739 (2014). Audio slides available at: http://audioslides.elsevier.com/getvideo.aspx?doi=10.1016/j.media.2014.04.001.
Burns JE, Yao J, Wiese T, Munoz H, Jones EC, Summers RM. Automated Detection of Sclerotic Metastases in the Thoracolumbar Spine at CT. Radiology 268(1):69-78 (2013). Images featured on the cover of the journal.
Zhang W, Liu J, Yao J, Louie A, Nguyen TB, Wank S, Nowinski WL, Summers RM. Mesenteric Vasculature-guided Small Bowel Segmentation on 3D CT. IEEE Transactions on Medical Imaging 32(11):2006-2021 (2013).
Nguyen TB, Wang SW, Anugu V, Rose N, McKenna M, Petrick N, Burns JE, Summers RM. Distributed Human Intelligence for Colonic Polyp Classification in Computer-aided Detection for CT Colonography. Radiology 262(3):824-833 (2012). Article highlighted in an accompanying video podcast at https://youtu.be/KPx1k3kK7_0.
Roney CA, Xu B, Xie J, Yuan S, Wierwille J, Chen C-W, Chen Y, Griffiths GL, and Summers RM. Rh-I-UEA-1 polymerized liposomes target and image adenomatous polyps in the APCMin/+ mouse using optical colonography. Molecular Imaging 10(4):305-316 (2011). Images featured on the cover of the journal.
Linguraru MG, Panjwani N, Fletcher JG, Summers RM. Automated Image-based Colon Cleansing for Laxative-free CT Colonography Computer-aided Polyp Detection. Med Phys 38(12):6633-6642 (2011). Article highlighted in the Editor's Picks column for the Medical Physics Scitation site.
Summers RM, Frentz S, Liu J, Yao J, Brown L, Louie A, Barlow DS, Jensen DW, Dwyer AJ, Pickhardt PJ, Petrick N. Conspicuity of Colorectal Polyps at CT Colonography: Visual Assessment, CAD Performance, and the Important Role of Polyp Height. Academic Radiology 16:4-14 (2009). [Article highlighted in an accompanying editorial: Krupinski EA. What can the radiologist teach CAD: lessons from CT colonoscopy. Academic Radiology 16:1-3 (2009).]
Summers RM, Swift JA, Dwyer AJ, Choi JR, Pickhardt PJ. Normalized Distance Along the Colon Centerline: A Method for Correlating Polyp Location on CT Colonography and Optical Colonoscopy. AJR 193:1296-1304 (2009). [Article highlighted in an accompanying editorial: Dachman AH. Comparison of Optical Colonoscopy and CT Colonography for Polyp Detection AJR 193:1289-1290 (2009).]
Petrick N, Haider M, Summers RM, Yeshwant SC, Brown L, Iuliano EM, Louie A, Choi JR, Pickhardt PJ. CT Colonography with Computer-Aided Detection as a Second Reader: Observer Performance Study. Radiology 246(1):148-156 (2008).
O’Connor SD, Yao J, Summers RM. Lytic Metastases in Thoracolumbar Spine: Computer Aided Detection at CT -- Preliminary Study. Radiology 242(3): 811-816 + supplemental material (2007). Images featured on the cover of the journal.
Huang A, Roy D, Summers RM, Franaszek M, Petrick N, Choi JR, Pickhardt PJ. Teniae Coli-Based Circumferential Localization System for CT Colonography: Feasibility Study. Radiology 243(2):551-560 (2007). See online movies at: http://radiology.rsnajnls.org/cgi/content/full/243/2/551/DC1.
Summers RM, Yao J, Pickhardt PJ, Franaszek M, Bitter I, Brickman D, Krishna V, Choi JR. Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population. Gastroenterology 129: 1832-1844 (2005). [Article highlighted in an accompanying editorial: Bond JH. Progress in refining virtual colonoscopy for colorectal cancer screening. Gastroenterology 129: 2103-2106 (2005).]
Finkelstein SE, Schrump DS, Nguyen DM, Hewitt SM, Kunst TF, Summers RM. Comparative evaluation of super-high resolution computed tomography and virtual bronchoscopy for the detection of tracheobronchial malignancies. Chest 124(5):1834-1840 (2003). See movies at http://www.chestjournal.org/cgi/content/full/124/5/1834/DC1
- NIH Clinical Center Director’s Award presented by Dr. James Gilman, 2017
- NIH Director’s Award, presented by NIH Director Dr. Francis Collins, 2012
- Presidential Early Career Award for Scientists and Engineers, presented by Dr. Neal Lane, President Clinton’s science advisor, 2000
NOTE: PDF documents require the free Adobe Reader.
This page last updated on 04/03/2019