Ehsan Samei, PhD

Professor of Radiology
Professor in the Department of Physics
Member of the Duke Cancer Institute
Professor of Biomedical Engineering
Professor in the Department of Electrical and Computer Engineering
Address: 2424 Erwin Road, Suite 302, Ravin Advanced Imaging Labs
Durham, NC 27705
Phone: (919) 684-7852

Research Interests

Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE, FIOMP, FACR is a Persian-American medical physicist. He is a tenured Professor of Radiology, Medical Physics, Biomedical Engineering, Physics, and Electrical and Computer Engineering at Duke University, where he also serves as the Chief Imaging Physicist for Duke University Health System, the director of the Carl E Ravin Advanced Imaging Laboratories, and the director of Center for Virtual Imaging Trials. He is certified by the American Board of Radiology, recognized as a Distinguished Investigator by the Academy of Radiology Research, and awarded Fellow by the American Association of Physicists in Medicine (AAPM), the International Society of Optics and Photonics (SPIE), the American Institute of Medical and Biomedical Engineering, International Organization of Medical Physics, and American College of Radiology. He was a founder or co-founder of the Duke Medical Physics Program, the Duke Imaging Physics Residency Program, the Duke Clinical Imaging Physics Group, the Center for Virtual Imaging Trials, and the Society of Directors of Academic Medical Physics Programs (SDAMPP). He has held senior leadership positions in the AAPM, SPIE, SDAMPP, and RSNA. 

Dr. Samei’s expertise include x-ray imaging, theoretical imaging models, simulation methods, and experimental techniques in medical image formation, analysis, assessment, and perception.  His current research includes methods to develop image quality and safety metrics that are clinically relevant and that can be used to design and utilize advanced imaging techniques towards optimum interpretive and quantitative performance. His research aims to bridge the gap between scientific scholarship and clinical practice, in the meaningful realization of translational research, and in clinical processes that are informed by scientific evidence. Those include advanced imaging performance characterization, procedural optimization, and radiomics in retrospective clinical dose and quality analytics. His most recent research interests have been virtual clinical trial across a broad spectrum of oncologic, pulmonary, cardiac, and vascular diseases, and developing  methodological advances that provide smart fusions of conventional, principle-informed and newer AI-based, data-informed approaches to scientific inquiry.

Dr. Samei has mentored over 100 trainees (graduate and postgraduate). He has over 1000 scientific publications including 300+ referred journal articles and 4 books. His laboratory of over 20 researchers has been supported continuously over years by 41 extramural grants, culminating in a NIH Program Project grant in 2021 to establish the national Center for Virtual Imaging Trials (CVIT), joining a small number of prominent Biomedical Technology Research Centers across the nation.


Hoye, Jocelyn, et al. “Correction for Systematic Bias in Radiomics Measurements Due to Variation in Imaging Protocols.Acad Radiol, vol. 29, no. 4, Apr. 2022, pp. e61–72. Pubmed, doi:10.1016/j.acra.2021.04.012.

Sugiura, Teruyo, et al. “Quantitative analysis of changes in lung density by dynamic chest radiography in association with CT values: a virtual imaging study and initial clinical corroboration.Radiol Phys Technol, vol. 15, no. 1, Mar. 2022, pp. 45–53. Pubmed, doi:10.1007/s12194-021-00648-w.

Sharma, Shobhit, et al. “A GPU-accelerated framework for individualized estimation of organ doses in digital tomosynthesis.Med Phys, vol. 49, no. 2, Feb. 2022, pp. 891–900. Pubmed, doi:10.1002/mp.15400.

Samei, Ehsan. “Medical physics 3.0: A renewed model for practicing medical physics in clinical imaging.Phys Med, vol. 94, Feb. 2022, pp. 53–57. Pubmed, doi:10.1016/j.ejmp.2021.12.020.

Jensen, Corey T., et al. “Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.Radiology, Jan. 2022, p. 211838. Pubmed, doi:10.1148/radiol.211838.

Tushar, Fakrul Islam, et al. “Classification of Multiple Diseases on Body CT Scans Using Weakly Supervised Deep Learning.Radiol Artif Intell, vol. 4, no. 1, Jan. 2022, p. e210026. Pubmed, doi:10.1148/ryai.210026.

Kanal, Kalpana M., et al. “U.S. Diagnostic Reference Levels and Achievable Doses for 10 Pediatric CT Examinations.Radiology, vol. 302, no. 1, Jan. 2022, pp. 164–74. Pubmed, doi:10.1148/radiol.2021211241.

Nelson, Jeffrey, et al. “Key Performance Indicators for Quality Imaging Practice: Why, What, and How.J Am Coll Radiol, vol. 19, no. 1 Pt A, Jan. 2022, pp. 4–12. Pubmed, doi:10.1016/j.jacr.2021.09.044.