IS
Shiri Lord, Isaac
Affiliation entities
Research groups
Title | Published in | Access level | OA Policy | Year | Views | Downloads | |
---|---|---|---|---|---|---|---|
Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging : a comprehensive deep learning study | European journal of nuclear medicine and molecular imaging | 2025 | 31 | 8 | |||
Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images | Physica medica | 2025 | 16 | 3 | |||
Deep Learning–Powered CT-Less Multitracer Organ Segmentation From PET Images | Clinical nuclear medicine | 2025 | 46 | 10 | |||
Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets : application to PET-based prediction of lung cancer subtypes | EJNMMI physics | 2025 | 2 | 1 | |||
Chronological age estimation for medico-legal expertise-based on sternoclavicular joint CT images using a deep neural network | Forensic imaging | 2025 | 30 | 11 | |||
Deep Radiogenomics Sequencing for Breast Tumor Gene-Phenotype Decoding Using Dynamic Contrast Magnetic Resonance Imaging | Molecular imaging and biology | 2025 | 21 | 6 | |||
Artificial intelligence-based cardiac transthyretin amyloidosis detection and scoring in scintigraphy imaging : multi-tracer, multi-scanner, and multi-center development and evaluation study | European journal of nuclear medicine and molecular imaging | 2025 | 18 | 7 | |||
The image biomarker standardization initiative : standardized convolutional filters for reproducible radiomics and enhanced clinical insights | Radiology | 2024 | 97 | 0 | |||
TMTV-Net : fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images — a multi-center generalizability analysis | European journal of nuclear medicine and molecular imaging | 2024 | 49 | 0 | |||
Organomics : A novel concept reflecting the importance of PET/CT healthy organ radiomics in non-small cell lung cancer prognosis prediction using machine learning | Clinical Nuclear Medicine | 2024 | 45 | 26 | |||
Fully automated explainable abdominal CT contrast media phase classification using organ segmentation and machine learning | Medical physics | 2024 | 66 | 42 | |||
Fully Automated Region-Specific Human-Perceptive-Equivalent Image Quality Assessment: Application to 18F-FDG PET Scans | Clinical nuclear medicine | 2024 | 39 | 25 | |||
Differentiation of COVID‐19 pneumonia from other lung diseases using CT radiomic features and machine learning : A large multicentric cohort study | International journal of imaging systems and technology | 2024 | 51 | 13 | |||
Segmentation-free outcome prediction from head and neck cancer PET/CT images : deep learning-based feature extraction from multi-angle maximum intensity projections (MA-MIPs) | Cancers | 2024 | 39 | 36 | |||
The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods | Annals of nuclear medicine | 2024 | 48 | 21 | |||
Deep transformer-based personalized dosimetry from SPECT/CT images: a hybrid approach for [177Lu]Lu-DOTATATE radiopharmaceutical therapy | European journal of nuclear medicine and molecular imaging | 2024 | 67 | 17 | |||
PRIMIS : Privacy-preserving medical image sharing via deep sparsifying transform learning with obfuscation | Journal of biomedical informatics | 2024 | 47 | 0 | |||
Differential privacy preserved federated learning for prognostic modeling in COVID‐19 patients using large multi‐institutional chest CT dataset | Medical physics | 2024 | 68 | 32 | |||
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 & biological engineering & computing | 2024 | 38 | 11 | |||
Theranostic digital twins : Concept, framework and roadmap towards personalized radiopharmaceutical therapies | Theranostics | 2024 | 60 | 37 | |||
Myocardial perfusion SPECT radiomic features reproducibility assessment : Impact of image reconstruction and harmonization | Medical physics | 2024 | 32 | 14 | |||
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 | Radiation oncology | 2024 | 38 | 18 | |||
Artificial intelligence-based analysis of whole-body bone scintigraphy: The quest for the optimal deep learning algorithm and comparison with human observer performance | Zeitschrift für medizinische Physik | 2024 | 78 | 48 | |||
Semi-supervised learning towards automated segmentation of PET images with limited annotations : application to lymphoma patients | Physical and Engineering Sciences in Medicine | 2024 | 53 | 0 | |||
Enhanced direct joint attenuation and scatter correction of whole-body PET images via context-aware deep networks | Zeitschrift für medizinische Physik | 2024 | 43 | 20 | |||
Information fusion for fully automated segmentation of head and neck tumors from PET and CT images | Medical physics | 2024 | 101 | 35 | |||
Real-time, acquisition parameter-free voxel-wise patient-specific Monte Carlo dose reconstruction in whole-body CT scanning using deep neural networks | European radiology | 2023 | 60 | 27 | |||
Multi-institutional PET/CT image segmentation using federated deep transformer learning | Computer methods and programs in biomedicine | 2023 | 69 | 34 | |||
The Clinical Added Value of Breast Cancer Imaging Using Hybrid PET/MR Imaging | Magnetic resonance imaging clinics of North America | 2023 | 53 | 2 | |||
Multi-Scale Temporal Imaging: From Micro- and Meso- to Macro-scale-time Nuclear Medicine | PET clinics | 2023 | 153 | 0 | |||
Dual-Centre Harmonised Multimodal Positron Emission Tomography/Computed Tomography Image Radiomic Features and Machine Learning Algorithms for Non-small Cell Lung Cancer Histopathological Subtype Phenotype Decoding | Clinical oncology | 2023 | 64 | 0 | |||
Multimodality medical image analysis using radiomics and deep learning | 2023 | 450 | 2 | ||||
Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study | Scientific reports | 2023 | 81 | 12 | |||
Artificial Intelligence-Driven Single-Shot PET Image Artifact Detection and Disentanglement: Toward Routine Clinical Image Quality Assurance | Clinical nuclear medicine | 2023 | 78 | 17 | |||
A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information | European Journal of Nuclear Medicine and Molecular Imaging | 2023 | 198 | 35 | |||
Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study | Journal of digital imaging | 2023 | 50 | 30 | |||
Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms | Journal of digital imaging | 2023 | 51 | 10 | |||
Tensor radiomics: paradigm for systematic incorporation of multi-flavoured radiomics features | Quantitative imaging in medicine and surgery | 2023 | 87 | 122 | |||
Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement | European journal of nuclear medicine and molecular imaging | 2023 | 116 | 24 | |||
Fully automated accurate patient positioning in computed tomography using anterior–posterior localizer images and a deep neural network: a dual-center study | European radiology | 2023 | 137 | 151 | |||
Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics | La Radiologia medica | 2023 | 87 | 57 | |||
Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning | European journal of nuclear medicine and molecular imaging | 2023 | 109 | 73 | |||
Myocardial Perfusion SPECT Imaging Radiomic Features and Machine Learning Algorithms for Cardiac Contractile Pattern Recognition | Journal of digital imaging | 2022 | 122 | 56 | |||
High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms | Scientific reports | 2022 | 148 | 64 | |||
COLI-Net: Deep learning-assisted fully automated COVID-19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images | International journal of imaging systems and technology | 2022 | 258 | 130 | |||
Deep‐TOF‐PET : Deep learning‐guided generation of time‐of‐flight from non‐TOF brain PET images in the image and projection domains | Human brain mapping | 2022 | 174 | 65 | |||
Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms | Journal of digital imaging | 2022 | 122 | 71 | |||
[18F]FDG-PET/CT radiomics and artificial intelligence in lung cancer: Technical aspects and potential clinical applications | Seminars in nuclear medicine | 2022 | 239 | 95 | |||
Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images | Computers in biology and medicine | 2022 | 166 | 64 | |||
Unsupervised pseudo CT generation using heterogenous multicentric CT/MR images and CycleGAN: Dosimetric assessment for 3D conformal radiotherapy | Computers in biology and medicine | 2022 | 168 | 0 | |||
Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics | Computers in biology and medicine | 2022 | 147 | 38 | |||
Overall survival prognostic modelling of non-small cell lung cancer patients using positron emission tomography/computed tomography harmonised radiomics features: the quest for the optimal machine learning algorithm | Clinical oncology | 2022 | 198 | 99 | |||
Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework | Clinical nuclear medicine | 2022 | 201 | 2 | |||
COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients | Computers in biology and medicine | 2022 | 262 | 108 | |||
Robust-Deep: A Method for Increasing Brain Imaging Datasets to Improve Deep Learning Models' Performance and Robustness | Journal of digital imaging | 2022 | 166 | 0 | |||
Synergistic impact of motion and acquisition/reconstruction parameters on 18F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies | Medical physics | 2022 | 100 | 45 | |||
Non-contrast Cine Cardiac Magnetic Resonance image radiomics features and machine learning algorithms for myocardial infarction detection | Computers in biology and medicine | 2022 | 240 | 171 | |||
Deep learning-based fully automated Z-axis coverage range definition from scout scans to eliminate overscanning in chest CT imaging | Insights into imaging | 2021 | 190 | 120 | |||
Treatment Response Prediction using MRI-based Pre-, Post- and Delta-Radiomic Features and Machine Learning Algorithms in Colorectal Cancer | Medical Physics | 2021 | 184 | 0 | |||
Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network | European Radiology | 2021 | 334 | 118 | |||
Fully Automated Gross Tumor Volume Delineation From PET in Head and Neck Cancer Using Deep Learning Algorithms | Clinical Nuclear Medicine | 2021 | 173 | 0 | |||
Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients | Computers in Biology and Medicine | 2021 | 272 | 111 | |||
Automatic fetal biometry prediction using a novel deep convolutional network architecture | Physica Medica | 2021 | 180 | 1 | |||
Whole-body voxel-based internal dosimetry using deep learning | European Journal of Nuclear Medicine and Molecular Imaging | 2021 | 292 | 187 | |||
Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study | Journal of Nuclear Cardiology | 2021 | 294 | 0 | |||
Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks | Journal of Nuclear Cardiology | 2021 | 262 | 0 | |||
Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging | European Journal of Nuclear Medicine and Molecular Imaging | 2021 | 285 | 116 | |||
Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information | Journal of Digital Imaging | 2021 | 217 | 84 | |||
Machine Learning-based Prognostic Modeling using Clinical Data and Quantitative Radiomic Features from Chest CT Images in COVID-19 Patients | Computers in Biology and Medicine | 2021 | 199 | 72 | |||
The promise of artificial intelligence and deep learning in PET and SPECT imaging | Physica Medica | 2021 | 220 | 216 | |||
Multi-level multi-modality (PET and CT) fusion radiomics: Prognostic modeling for non-small cell lung carcinoma | Physics in medicine and biology | 2021 | 209 | 0 | |||
Non-Small Cell Lung Carcinoma Histopathological Subtype Phenotyping using High-Dimensional Multinomial Multiclass CT Radiomics Signature | Computers in Biology and Medicine | 2021 | 185 | 155 | |||
Artificial intelligence-driven assessment of radiological images for COVID-19 | Computers in Biology and Medicine | 2021 | 175 | 382 | |||
DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms | NeuroImage | 2021 | 188 | 104 | |||
Deep learning-based Auto-segmentation of Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer | Radiotherapy and Oncology | 2021 | 178 | 0 | |||
Personalized brachytherapy dose reconstruction using deep learning | Computers in Biology and Medicine | 2021 | 171 | 132 | |||
Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms | Molecular Imaging and Biology | 2020 | 249 | 0 | |||
Radiomics for classification of bone mineral loss: A machine learning study | Diagnostic and Interventional Imaging | 2020 | 286 | 362 | |||
A theranostic approach based on radiolabeled antiviral drugs, antibodies and CRISPR-associated proteins for early detection and treatment of SARS-CoV-2 disease | Nuclear Medicine Communications | 2020 | 301 | 237 | |||
Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network | European Journal of Nuclear Medicine and Molecular Imaging | 2020 | 240 | 0 | |||
Low Dose Radiation Therapy and Convalescent Plasma: How a Hybrid Method May Maximize Benefits for COVID-19 Patients | Journal of Biomedical Physics and Engineering | 2020 | 337 | 119 | |||
Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning | La Radiologia Medica | 2020 | 307 | 1 | |||
Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: test-retest and image registration analyses | Medical Physics | 2020 | 268 | 1 | |||
Deep Learning-based Automated Delineation of Head and Neck Malignant Lesions from PET Images | 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) | 2020 | 221 | 0 |