Tanaka R, Segars W, Abadi E, Minami S, Samei E.
Optimization of imaging conditions in pediatric dynamic chest radiography: a virtual imaging trial.
SPIE Medical Imaging. 2022;12031.
https://doi.org/10.1117/12.2612720
Tushar FI, Abadi E, Sotoudeh-Paima S, Fricks R, Mazurowski M, Segars WP, Samei E, Lo J.
Virtual vs. reality: external validation of COVID-19 classifiers using XCAT phantoms for chest computed tomography.
SPIE Medical Imaging. 2022;12033.
Tushar FI, D’Anniballe V, Rubin G, Samei E, Lo J.
Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CT.
SPIE Medical Imaging. 2022;12033
https://doi.org/10.1117/12.2612700
Tushar FI, Nujaim H, Fu W, Abadi E, Mazurowski M, Segars W, Samei E, Lo JY.
Quality or quantity: toward a unified approach for multi-organ segmentation in body CT.
SPIE Medical Imaging. 2022;12031.
Quality or quantity: toward a unified approach for multi-organ segmentation in body CT Read More »
Zarei M, Sotoudeh-Paima S, Abadi E, Samei E.
A truth-based primal-dual learning approach to reconstruct CT images utilizing the virtual imaging trial platform.
SPIE Medical Imaging. 2022;12031.
https://doi.org/10.1117/12.2613168
Fricks R, Abadi E, Ria F, Samei E.
Classification of COVID-19 in chest radiographs: assessing the impact of imaging parameters using clinical and simulated images.
SPIE Medical Imaging. .2021;11597. [Foundation]
https://doi.org/10.1117/12.2582223
Jadick G, Abadi E, Harrawood B, Sharma S, Segars WP, Samei E.
A framework to simulate CT images with tube current modulation.
SPIE Medical Imaging. .2021;11595. [Foundation]
https://doi.org/10.1117/12.2580983
A framework to simulate CT images with tube current modulation Read More »
Zarei M, Abadi E, Fricks R, Segars WP, Samei E.
A probabilistic conditional adversarial neural network to reduce imaging variation in radiography.
SPIE Medical Imaging. .2021;11595. [Foundation]
https://doi.org/10.1117/12.2582336
Zarei M, Abadi E, Segars WP, Richards T, Samei E.
Multi-factorial optimization of imaging parameters for quantifying coronary stenosis in cardiac CT.
SPIE Medical Imaging. .2021;11595. [Foundation]
https://doi.org/10.1117/12.2582311
Sauer T, Abadi E, Segars WP, Samei E.
Optimization of CT angiography using physiologically-informed computational plaques, dynamic XCAT phantoms, and physics-based CT simulation.
SPIE Medical Imaging. .2021;11595. [Foundation]
https://doi.org/10.1117/12.2582293
