TRD3

Duke Lung Cancer Screening (DLCS) Dataset: A Reference Dataset of Annotated Low-dose Screening Thoracic CT.

Wang AJ, Tushar FI, Harowicz MR, Tong BC, Lafata KJ, Tailor TD, Lo JY.
Duke Lung Cancer Screening (DLCS) Dataset: A Reference Dataset of Annotated Low-dose Screening Thoracic CT.
Radiology Artificial Intelligence.2025;e240248 Epub 2025/04/16. [Foundation]
https://doi.org/10.1148/ryai.240248

Duke Lung Cancer Screening (DLCS) Dataset: A Reference Dataset of Annotated Low-dose Screening Thoracic CT. Read More »

Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection.

Tushar FI, Vancoillie L, McCabe C, Kavuri A, Dahal L, Harrawood B, Fryling M, Zarei M, Sotoudeh-Paima S, et al.
Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection.
Medical Image Analysis.2025;103:103576 Epub 2025/04/05. [Foundation]
https://doi.org/10.1016/j.media.2025.103576

Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection. Read More »

Protocol selection formalism for minimizing detectable differences in morphological radiomics features of lung lesions in repeated CT acquisitions

Zarei M, Abadi E, Vancoillie L, Samei E.
Protocol selection formalism for minimizing detectable differences in morphological radiomics features of lung lesions in repeated CT acquisitions.
Journal of Medical Imaging. 2024;11(2)025501. Epub 2024/04/26.[Foundation]
https://doi.org/10.1117/1.JMI.11.2.025501

Protocol selection formalism for minimizing detectable differences in morphological radiomics features of lung lesions in repeated CT acquisitions Read More »

Optimization of imaging parameters of an investigational photon-counting CT prototype for lung lesion radiomics

McCabe C, Zarei M, Segars WP, Samei E, Abadi E.
Optimization of imaging parameters of an investigational photon-counting CT prototype for lung lesion radiomics.
SPIE Medical Imaging. 2022;12033.
https://doi.org/10.1117/12.2612973

Optimization of imaging parameters of an investigational photon-counting CT prototype for lung lesion radiomics Read More »

Virtual vs. reality: external validation of COVID-19 classifiers using XCAT phantoms for chest computed tomography

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.

Virtual vs. reality: external validation of COVID-19 classifiers using XCAT phantoms for chest computed tomography Read More »

Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CT

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

Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CT Read More »