M. Oveisi

Azin Alizadehasl, Mehrdad Oveisi, Isaac Shiri, 2019, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study

M. S. Zafarghandi, Hossein ARABI, H. Abdollahi, 2019, Journal of Nuclear Cardiology.

Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

M. Deevband, M. Nazari, H. Abdollahi, 2019, La radiologia medica.

Myocardial Perfusion SPECT Imaging Radiomic Features and Machine Learning Algorithms for Cardiac Contractile Pattern Recognition

H. Zaidi, M. Oveisi, G. Hajianfar, 2022, Journal of Digital 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.

Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches

Hassan Maleki, Arman Rahmim, Mehrdad Oveisi, 2019, ArXiv.

Late Gadolinium Enhanced Cardiac Magnetic Resonance Imaging Radiomics For High Precision Differentiation of Scar and Viable Cardiac Tissues

H. Zaidi, M. Deevband, H. Abdollahi, 2020, 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

Mohammad Reza Deevband, Mehrdad Oveisi, Mostafa Nazari, 2019, La radiologia medica.

PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients

Hassan Maleki, Arman Rahmim, Mehrdad Oveisi, 2018, 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC).

Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms

M. Hatt, A. Rahmim, S. Ashrafinia, 2019, Molecular Imaging and Biology.

Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics.

M. Nazari, Isaac Shiri, M. Oveisi, 2023, La Radiologia medica.

Assessment of Machine Learning Approaches to Predict in-Hospital Mortality in Patients Underwent Prosthetic Heart Valve Replacement Surgery

Isaac Shiri, M. Oveisi, G. Hajianfar, 2023, Journal of Advances in Medical and Biomedical 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..

ComBat Harmonization of Image Reconstruction Parameters to Improve the Repeatability of Radiomics Features

H. Zaidi, P. Geramifar, M. Oveisi, 2021, Nuclear Science Symposium and Medical Imaging Conference.

Histopathological Subtype Phenotype Decoding Using Harmonized PET/CT Image Radiomics Features and Machine Learning

H. Zaidi, M. Oveisi, G. Hajianfar, 2021, Nuclear Science Symposium and Medical Imaging Conference.

Prediction of Myocardial Function after Coronary Artery Bypass Graft using Cardiac Magnetic Resonance Imaging Radiomics

H. Zaidi, S. Mostafaei, M. Oveisi, 2021, Nuclear Science Symposium and Medical Imaging Conference.

Comparison of Machine Learning Algorithms Using Manual/Automated Features on 12-Lead Signal Electrocardiogram Classification: A Large Cohort Study on Students Aged Between 6 to 18 Years Old

Isaac Shiri, M. Oveisi, M. Khorgami, 2023, Cardiovascular engineering and technology.

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).

Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study.

M. Oveisi, G. Hajianfar, I. Shiri, 2024, Medical & biological engineering & computing.

Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC)

Kevin H. Leung, A. Rahmim, M. Ay, 2019, European Radiology.