Title:

Medical Physics: Now and Prospects Ahead

Speaker:

Dr. Ehsan Samei

Affiliation:

Duke University

When:

Thursday, September 28, 2023 at 11:00:00 AM   Add to Calendar

Where:

Boggs Building, Room 3-47

Host:

Chris Wang
chris.wang@nre.gatech.edu

Abstract

N/A

Biography

Dr. Ehsan Samei, is the Reed and Martha Rice distinguished Professor of Radiology, and Professor of 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 five professional organization. He founded/cofounded 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, including election to the presidency of the SEAAPM (2010-2011), SDAMPP (2011), and AAPM (2023). Dr. Samei scientific expertise include x-ray imaging, theoretical imaging models, simulation methods, and experimental techniques in medical image formation, quantification, and perception. His research aims to bridge the gap between scientific scholarship and clinical practice. He has advanced image quality and safety metrics and radiometrics that are clinically relevant. Many techniques he developed have been implemented in advanced imaging performance characterization, procedural optimization, and clinical dose and quality analytics. His most recent research interests have been virtual clinical trial across abroad spectrum of oncologic, pulmonary, cardiac, and vascular diseases, and developing methodological advances that provide smart fusions of principle-informed and AI-based, data informed approaches to scientific inquiry.

Notes

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