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
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 CiteOptimizing 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 CitePrecise 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 CiteRecent Grants
Evaluate clinically the quantitative performance of Siementoms, the quantitative performance of Siemens PCD CT scanner (NAEOTOM Alpha) for longitudinal chest imaging in comparison to EID CT scanners.
Clinical TrialPrincipal Investigator · Awarded by Siemens Medical Solutions USA, Inc. · 2025 - 2028Quantitative and Qualitative Evaluation of a Novel Motion Correction Algorithm for Brain and Chest CT Imaging
ResearchPrincipal Investigator · Awarded by GE Precision Healthcare LLC · 2026 - 2027Accuracy and Precision in CT Quantification of COPD Through Virtual Imaging Trials
ResearchPrincipal Investigator · Awarded by National Heart, Lung, and Blood Institute · 2021 - 2027View All Grants