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Ehsan Abadi

Associate Professor in Radiology
Radiology

Overview


Ehsan Abadi, PhD is an imaging scientist at Duke University. He serves as an Associate Professor in the departments of Radiology and Electrical & Computer Engineering, a faculty member in the Medical Physics Graduate Program and Carl E. Ravin Advanced Imaging Laboratories, and a co-Lead in the Center for Virtual Imaging Trials. Ehsan’s research focuses on quantitative imaging and optimization, computational human modeling, medical imaging simulation, and CT imaging in cardiothoracic and musculoskeletal applications. He is actively involved in developing computational anthropomorphic models with various diseases such as COPD, and scanner-specific simulation platforms (e.g., DukeSim) for imaging systems. Currently, his work is centered on identifying and optimizing imaging systems to ensure accurate and precise quantifications of lung and bone diseases.

Current Duke Appointments & Affiliations


Associate Professor in Radiology · 2024 - Present Radiology, Clinical Science Departments
Associate Professor in the Department of Electrical and Computer Engineering · 2024 - Present Pierre R. Lamond Department of Electrical and Computer Engineering, Pratt School of Engineering

Recent Scholarly Works


Proton therapy range uncertainty reduction using vendor-agnostic tissue characterization on a virtual photon-counting CT head scan.

Journal article Med Phys · May 2026 BACKGROUND: Photon-counting CT (PCCT) is the latest technology enabling imaging with reduced noise and inherent spectral separation, with the potential to directly calculate a more accurate tissue stopping power from spectral data. This potential benefit i ... Full text Link to item Cite

Optimizing energy settings in CdTe, CZT, and Si photon-counting CT for material separation and detection.

Journal article Phys Med Biol · April 8, 2026 Objective. The performance of photon-counting CT (PCCT) depends on how detector energy thresholds or bins (collectively referred to as energy settings) are defined. This study aimed to identify optimal energy settings for various PCCT technologies to enhan ... Full text Link to item Cite

Precise Lung Density Quantification with a Physics-based CT Harmonizer.

Journal article Radiol Cardiothorac Imaging · April 2026 Purpose To develop a physics-based image harmonization method that transforms images into a reference quality index of noise, spatial resolution, and lung volume and to evaluate its performance for improving reproducibility of lung density measurement. Mat ... Full text Link to item Cite
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Recent Grants


Quantitative and Qualitative Evaluation of a Novel Motion Correction Algorithm for Brain and Chest CT Imaging

ResearchPrincipal Investigator · Awarded by GE Precision Healthcare LLC · 2026 - 2027

Accuracy and Precision in CT Quantification of COPD Through Virtual Imaging Trials

ResearchPrincipal Investigator · Awarded by National Heart, Lung, and Blood Institute · 2021 - 2027

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Education


Duke University · 2018 Ph.D.