20 citations · 44 across the 6 of their papers we have counts for
7 papers
A novel shape-based loss function for machine learning-based seminal organ segmentation in medical imaging
Reza Karimzadeh, Emad Fatemizadeh, Hossein Arabi
Automated medical image segmentation is an essential task to aid/speed up diagnosis and treatment procedures in clinical practices. Deep convolutional neural networks have exhibite…
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…
Quantitative and Qualitative Performance Evaluation of Commercial Metal Artifact Reduction Methods: Dosimetric Effects on the Treatment Planning
Mohammad Ghorbanzadeh, Seyed Abolfazl Hosseini, Bijan Vosoughi Vahdat +3
The presence of metal implants within CT imaging causes severe attenuation of the X-ray beam. Due to the incomplete information recorded by CT detectors, artifacts in the form of s…
Comparison of different deep learning architectures for synthetic CT generation from MR images
Abbas Bahrami, Alireza Karimian, Hossein Arabi
MRI-guided radiation treatment planning is widely applied because of its superior soft-tissue contrast and no ionization radiation compared to CT-based planning. In this regard, sy…
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…
Deep learning-based noise reduction in low dose SPECT Myocardial Perfusion Imaging: Quantitative assessment and clinical performance
Narges Aghakhan Olia, Alireza Kamali-Asl1, Sanaz Hariri Tabrizi +4
Clinical SPECT-MPI images of 345 patients acquired from a dedicated cardiac SPECT in list-mode format were retrospectively employed to predict normal-dose images from low-dose data…