Faeze Gholamiankhah

A Novel Unsupervised COVID-19 Lesion Segmentation from CT Images Based-on the Lung Tissue Detection

H. Zaidi, S. Mostafapour, N. Goushbolagh, 2021, 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

The impact of MR-guided attenuation correction (compared to CT-based AC) on the diagnosis of anosmia based on 99m-Tc Ethyl-Cysteinate-Dimer SPECT images

Hossein ARABI, S. Mostafapour, A. Parach, 2021, International Journal of Radiation Research.

Deep learning-based attenuation correction in the image domain for myocardial perfusion SPECT imaging

Hossein Arabi, Seyed Rasoul Zakavi, Mahdi Momennezhad, 2021, 2102.04915.

Deep learning-based synthetic CT generation from MR images: comparison of generative adversarial and residual neural networks

Hossein ARABI, S. Mostafapour, Faeze Gholamiankhah, 2021, International Journal of Radiation Research.

Automated Lung Segmentation from Computed Tomography Images of Normal and COVID-19 Pneumonia Patients

S. Tabatabaei, S. Mostafapour, P. Layegh, 2022, Iranian journal of medical sciences.

Attenuation Correction for Myocardial Perfusion SPECT Imaging in the Image Domain

H. Zaidi, M. Momennezhad, S. Mostafapour, 2021, 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

Automated lung segmentation from CT images of normal and COVID-19 pneumonia patients

Hossein Arabi, S. Tabatabaei, S. Mostafapour, 2021, ArXiv.

Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain

H. Zaidi, Hossein ARABI, S. Mostafapour, 2021, Clinical nuclear medicine.