Z. Mansouri

发表

Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network

H. Zaidi, Hossein ARABI, H. Abdollahi, 2020, European Radiology.

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.

Fully automated accurate patient positioning in computed tomography using anterior–posterior localizer images and a deep neural network: a dual-center study

H. Zaidi, Y. Salimi, Z. Mansouri, 2023, European Radiology.

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).

Predictive value of 99mTc-MAA-based dosimetry in personalized 90Y-SIRT planning for liver malignancies

V. Garibotto, A. Akhavanallaf, Y. Salimi, 2023, EJNMMI Research.

Development and validation of survival prognostic models for head and neck cancer patients using machine learning and dosiomics and CT radiomics features: a multicentric study

Y. Salimi, Z. Mansouri, M. Oveisi, 2024, Radiation oncology.

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..

Information fusion for fully automated segmentation of head and neck tumors from PET and CT images.

A. Rahmim, Y. Salimi, Z. Mansouri, 2023, Medical Physics (Lancaster).

Interpretable PET/CT Radiomic Based Prognosis Modeling of NSCLC Recurrent Following Complete Resection

Z. Mansouri, I. Shiri, Saikat Chatterjee, 2022, 2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

Deep learning-assisted multiple organ segmentation from whole-body CT images

Z. Mansouri, I. Shiri, Y. Salimi, 2023, medRxiv.

Real-time, acquisition parameter-free voxel-wise patient-specific Monte Carlo dose reconstruction in whole-body CT scanning using deep neural networks

A. Akhavanallaf, Y. Salimi, Z. Mansouri, 2023, European Radiology.

Fully Automated Explainable Abdominal CT Contrast Media Phase Classification Using Organ Segmentation and Machine Learning

Y. Salimi, Z. Mansouri, G. Hajianfar, 2023, medRxiv.

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).

The role of biomarkers and dosimetry parameters in overall and progression free survival prediction for patients treated with personalized 90Y glass microspheres SIRT: a preliminary machine learning study.

Y. Salimi, Z. Mansouri, G. Hajianfar, 2024, European journal of nuclear medicine and molecular imaging.