Multi-Scale Convolutional Neural Network for Automated AMD Classification using Retinal OCT Images

no code implementations • 6 Oct 2021 • Saman Sotoudeh-Paima, Ata Jodeiri, Fedra Hajizadeh, Hamid Soltanian-Zadeh

The workload of specialists and the healthcare system in this field has increased in recent years mainly due to the prevalence of population aging worldwide and the chronic nature of AMD.

Virtual vs. Reality: External Validation of COVID-19 Classifiers using XCAT Phantoms for Chest Computed Tomography

no code implementations • 7 Mar 2022 • Fakrul Islam Tushar, Ehsan Abadi, Saman Sotoudeh-Paima, Rafael B. Fricks, Maciej A. Mazurowski, W. Paul Segars, Ehsan Samei, Joseph Y. Lo

However, performance dropped to an AUC of 0. 65 and 0. 69 when evaluated on clinical and our simulated CVIT-COVID dataset.

Computed Tomography (CT) COVID-19 Diagnosis

Virtual imaging trials improved the transparency and reliability of AI systems in COVID-19 imaging

1 code implementation • 17 Aug 2023 • Fakrul Islam Tushar, Lavsen Dahal, Saman Sotoudeh-Paima, Ehsan Abadi, W. Paul Segars, Ehsan Samei, Joseph Y. Lo

In this study, COVID-19 serves as a case example to unveil the intrinsic and extrinsic factors influencing AI performance.

Computed Tomography (CT) COVID-19 Diagnosis

VLST: Virtual Lung Screening Trial for Lung Cancer Detection Using Virtual Imaging Trial

no code implementations • 17 Apr 2024 • Fakrul Islam Tushar, Liesbeth Vancoillie, Cindy McCabe, Amareswararao Kavuri, Lavsen Dahal, Brian Harrawood, Milo Fryling, Mojtaba Zarei, Saman Sotoudeh-Paima, Fong Chi Ho, Dhrubajyoti Ghosh, Sheng Luo, W. Paul Segars, Ehsan Abadi, Kyle J. Lafata, Ehsan Samei, Joseph Y. Lo

Objectives: To establish a virtual imaging trial (VIT) platform that accurately simulates real-world lung screening trials (LSTs) to assess the diagnostic accuracy of CT and CXR modalities.