Ehsan Samei

Ehsan Samei

Professor of Radiology

Professor in the Department of Physics (Secondary)

Member of the Duke Cancer Institute

Professor in the Department of Electrical and Computer Engineering (Secondary)

Office Location: 
2424 Erwin Road, Suite 302, Ravin Advanced Imaging Labs, Durham, NC 27705
Front Office Address: 
DUMC Box 2731, Durham, NC 27710
Phone: 
(919) 684-7852

Overview

Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE 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. He serves as the Director of the Duke Medical Physics Graduate Program and the Director of the Clinical Imaging Physics Group. He is certified by the American Board of Radiology, and is a Fellow of the American Association of Physicists in Medicine (AAPM), the International Society of Optics and Phtonics (SPIE), and the American Institute of Biomedical Engineering. He is a Councilor of the National Council of Radiation Protection and Measurements (NCRP), and a Distinguished Investigator of the Academy of Radiology Research. He was the founder or co-founder of the Duke Medical Physics Program, the Duke Imaging Physics Residency Program, the Duke Clinical Imaging Physics Group, 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 interests and 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 dose metrics that are clinically relevant and that can be used to design and utilize advanced imaging techniques towards optimum interpretive and quantitative performance. He further has an active interest in bridging 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. He has mentored over 100 trainees (graduate and postgraduate). He has over 900 scientific publications including over 240 referred journal articles. He has been the recipient of 34 grants as Principle Investigator reflecting $13M of extramural funding.

Education & Training

  • Ph.D., University of Michigan, Ann Arbor 1997

  • M.E., University of Michigan, Ann Arbor 1995

Selected Grants

Reconstruction Software Evaluation awarded by Siemens Medical Solutions USA, Inc. (Principal Investigator). 2014 to 2018

Methodology and Reference Image set for Volumetric Characterization and Compliance awarded by Radiological Society of North America (Principal Investigator). 2014 to 2017

Reference Image Set for Quantitation Conformance of Algorithmic Lesion Characterization awarded by Radiological Society of North America (Principal Investigator). 2014 to 2017

Advancement and Effective Implementation of Dose and Risk Monitoring Systems awarded by GE Healthcare (Principal Investigator). 2014 to 2017

Decreased Variability for Robust Imaging-based Quantification of Tumor Heterogeneity awarded by Radiological Society of North America (Advisor). 2015 to 2017

IAEA scientific visit and training awarded by International Atomic Energy Agency (Principal Investigator). 2016

Duke Clinical Imaging Physics Group Fellowship awarded by Bracco Foundation (Principal Investigator). 2015 to 2016

X-Ray Scatter and Phase Imaging for Explosive Detection awarded by US Department of Homeland Security (Co-Principal Investigator). 2011 to 2015

3D Digital Breast Phantoms For Multimodality Research awarded by National Institutes of Health (Collaborator). 2010 to 2014

Pages

Cheng, Yuan, et al. “Correlation of Algorithmic and Visual Assessment of Lesion Detection in Clinical Images.Acad Radiol, vol. 27, no. 6, June 2020, pp. 847–55. Pubmed, doi:10.1016/j.acra.2019.07.015. Full Text

Ria, Francesco, et al. “Technical Note: Validation of TG 233 phantom methodology to characterize noise and dose in patient CT data.Med Phys, vol. 47, no. 4, Apr. 2020, pp. 1633–39. Pubmed, doi:10.1002/mp.14089. Full Text Open Access Copy

Nelson, Jeffrey S., and Ehsan Samei. “Automated quality control in nuclear medicine using the structured noise index.J Appl Clin Med Phys, vol. 21, no. 4, Apr. 2020, pp. 80–86. Pubmed, doi:10.1002/acm2.12850. Full Text

Tushar, Fakrul Islam, et al. “Weakly Supervised Multi-Organ Multi-Disease Classification of Body CT Scans.Corr, vol. abs/2008.01158, 2020.

Setiawan, H., et al. “Patient-informed modelling of hepatic contrast dynamics in contrast-enhanced CT imaging.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 11312, Jan. 2020. Scopus, doi:10.1117/12.2548879. Full Text Open Access Copy

Meyer, Mathias, et al. “Reproducibility of CT Radiomic Features within the Same Patient: Influence of Radiation Dose and CT Reconstruction Settings.Radiology, vol. 293, no. 3, Dec. 2019, pp. 583–91. Pubmed, doi:10.1148/radiol.2019190928. Full Text

Sharma, Shobhit, et al. “A real-time Monte Carlo tool for individualized dose estimations in clinical CT.Phys Med Biol, vol. 64, no. 21, Nov. 2019, p. 215020. Pubmed, doi:10.1088/1361-6560/ab467f. Full Text

Cheng, Yuan, et al. “Validation of algorithmic CT image quality metrics with preferences of radiologists.Med Phys, vol. 46, no. 11, Nov. 2019, pp. 4837–46. Pubmed, doi:10.1002/mp.13795. Full Text Open Access Copy

Hoye, Jocelyn, et al. “Organ doses from CT localizer radiographs: Development, validation, and application of a Monte Carlo estimation technique.Med Phys, vol. 46, no. 11, Nov. 2019, pp. 5262–72. Pubmed, doi:10.1002/mp.13781. Full Text Open Access Copy

Pages

Kanal, Kalpana, et al. “How International Actions Interface and Support Med Phys 3.0.” Medical Physics, vol. 46, no. 6, WILEY, 2019, pp. E255–56.

Richards, Taylor W., et al. “Cardiac CT estimability index: an ideal estimator in the presence of noise and motion.” Medical Imaging 2019: Physics of Medical Imaging, SPIE, 2019. Crossref, doi:10.1117/12.2513035. Full Text

Abadi, E., et al. “A framework for realistic virtual clinical trials in photon counting computed tomography.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10948, 2019. Scopus, doi:10.1117/12.2512898. Full Text

Fu, W., et al. “Multi-organ segmentation in clinical-computed tomography for patient-specific image quality and dose metrology.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10948, 2019. Scopus, doi:10.1117/12.2512883. Full Text

Setiawan, H., et al. “Patient-informed and physiology-based modelling of contrast dynamics in cross-sectional imaging.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10948, 2019. Scopus, doi:10.1117/12.2513431. Full Text

Sauer, T. J., et al. “Anatomically- and computationally-informed hepatic contrast perfusion simulations for use in virtual clinical trials.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10948, 2019. Scopus, doi:10.1117/12.2513465. Full Text

Pegues, H., et al. “Using inkjet 3D printing to create contrast-enhanced textured physical phantoms for CT.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10948, 2019. Scopus, doi:10.1117/12.2512890. Full Text

Liu, Y., et al. “Deep learning of 3D computed tomography (CT) images for organ segmentation using 2D multi-channel SegNet model.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10954, 2019. Scopus, doi:10.1117/12.2512887. Full Text

Veress, A. I., et al. “Utilizing deformable image registration to create new living human heart models for imaging simulation.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 10948, 2019. Scopus, doi:10.1117/12.2512939. Full Text

Pages