Isaac Shiri
Orcid: 0000-0002-5735-0736
According to our database1,
Isaac Shiri
authored at least 31 papers
between 2019 and 2024.
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Bibliography
2024
Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study.
Medical Biol. Eng. Comput., August, 2024
Differentiation of COVID-19 pneumonia from other lung diseases using CT radiomic features and machine learning: A large multicentric cohort study.
Int. J. Imaging Syst. Technol., March, 2024
PRIMIS: Privacy-preserving medical image sharing via deep sparsifying transform learning with obfuscation.
J. Biomed. Informatics, 2024
Segmentation-Free Outcome Prediction in Head and Neck Cancer: Deep Learning-based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs) of PET Images.
CoRR, 2024
2023
Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms.
J. Digit. Imaging, December, 2023
Multi-institutional PET/CT image segmentation using federated deep transformer learning.
Comput. Methods Programs Biomed., October, 2023
Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study.
J. Digit. Imaging, August, 2023
Deep Learning-based Non-rigid Image Registration for High-dose Rate Brachytherapy in Inter-fraction Cervical Cancer.
J. Digit. Imaging, April, 2023
Myocardial Perfusion SPECT Imaging Radiomic Features and Machine Learning Algorithms for Cardiac Contractile Pattern Recognition.
J. Digit. Imaging, April, 2023
PhD thesis, 2023
2022
Robust-Deep: A Method for Increasing Brain Imaging Datasets to Improve Deep Learning Models' Performance and Robustness.
J. Digit. Imaging, 2022
Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.
J. Digit. Imaging, 2022
COLI-Net: Deep learning-assisted fully automated COVID-19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images.
Int. J. Imaging Syst. Technol., 2022
Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features.
CoRR, 2022
COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14, 339 patients.
Comput. Biol. Medicine, 2022
Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images.
Comput. Biol. Medicine, 2022
Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics.
Comput. Biol. Medicine, 2022
Unsupervised pseudo CT generation using heterogenous multicentric CT/MR images and CycleGAN: Dosimetric assessment for 3D conformal radiotherapy.
Comput. Biol. Medicine, 2022
Non-contrast Cine Cardiac Magnetic Resonance image radiomics features and machine learning algorithms for myocardial infarction detection.
Comput. Biol. Medicine, 2022
2021
DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms.
NeuroImage, 2021
Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information.
J. Digit. Imaging, 2021
Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients.
Comput. Biol. Medicine, 2021
Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients.
Comput. Biol. Medicine, 2021
Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature.
Comput. Biol. Medicine, 2021
Comput. Biol. Medicine, 2021
Comput. Biol. Medicine, 2021
2019
Non-Invasive Fuhrman Grading of Clear Cell Renal Cell Carcinoma Using Computed Tomography Radiomics Features and Machine Learning.
CoRR, 2019
Non-Invasive MGMT Status Prediction in GBM Cancer Using Magnetic Resonance Images (MRI) Radiomics Features: Univariate and Multivariate Machine Learning Radiogenomics Analysis.
CoRR, 2019
Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches.
CoRR, 2019
MFP-Unet: A Novel Deep Learning Based Approach for Left Ventricle Segmentation in Echocardiography.
CoRR, 2019
PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients.
CoRR, 2019