14 citations · 26 across the 3 of their papers we have counts for
3 papers
A novel unsupervised covid lung lesion segmentation based on the lung tissue identification
Faeze Gholamian Khah, Samaneh Mostafapour, Seyedjafar Shojaerazavi +2
This study aimed to evaluate the performance of a novel unsupervised deep learning-based framework for automated infections lesion segmentation from CT images of Covid patients. In…
Automated lung segmentation from CT images of normal and COVID-19 pneumonia patients
Faeze Gholamiankhah, Samaneh Mostafapour, Nouraddin Abdi Goushbolagh +4
Automated semantic image segmentation is an essential step in quantitative image analysis and disease diagnosis. This study investigates the performance of a deep learning-based mo…
Quantitative analysis of image quality in low-dose CT imaging for Covid-19 patients
Behrooz Ghane, Alireza Karimian, Samaneh Mostafapour +3
We set out to simulate four reduced dose-levels (60%-dose, 40%-dose, 20%-dose, and 10%-dose) of standard CT imaging using Beer-Lambert's law across 49 patients infected with COVID-…