M. Pakbin

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization.

H. Zaidi, Hossein ARABI, A. Akhavanallaf, 2022, European journal of radiology.

COLI‐Net: Deep learning‐assisted fully automated COVID‐19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images

H. Zaidi, H. Abdollahi, Isaac Shiri, 2021, Int. J. Imaging Syst. Technol..

COLI-NET: Fully Automated COVID-19 Lung and Infection Pneumonia Lesion Detection and Segmentation from Chest CT Images

H. Zaidi, Hossein ARABI, H. Abdollahi, 2021, medRxiv.

COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients

A. Saberi, A. Akhavanallaf, Y. Salimi, 2021, Computers in Biology and Medicine.

Deep learning-based fully automated Z-axis coverage range definition from scout scans to eliminate overscanning in chest CT imaging

H. Zaidi, Isaac Shiri, A. Akhavanallaf, 2021, Insights into Imaging.

Diagnosis of COVID-19 Using CT image Radiomics Features: A Comprehensive Machine Learning Study Involving 26,307 Patients

A. Rahmim, H. Zaidi, P. Geramifar, 2021, medRxiv.

Deep Learning-based Fully Automated Scan Range Detection in Chest CT Imaging

H. Zaidi, Hossein ARABI, A. Akhavanallaf, 2021, 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

Differentiation of COVID‐19 pneumonia from other lung diseases using CT radiomic features and machine learning: A large multicentric cohort study

P. Geramifar, A. Saberi, A. Akhavanallaf, 2024, Int. J. Imaging Syst. Technol..

Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset.

Mostafa Ghelich Oghli, Y. Salimi, D. Askari, 2024, Medical Physics (Lancaster).