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Publicações de Mario Jreige ordenado por recente
| , , , , , , , , , , , and , Multi-Method eXplainability for Similarity Assessment in AI-Denoised PET Imaging, in: IEEE International Symposium on Biomedical Imaging (ISBI), 2026 |
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , A Multimodal and Multi-centric Head and Neck Cancer Dataset for Tumor Segmentation and Outcome Prediction (2025) |
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| , , , , , , , , , , and , Contribution of Quantitative I-123-ioflupane SPECT/CT to the Differential Diagnosis of Dementia with Lewy Bodies (2025), in: European Journal of Nuclear Medicine and Molecular Imaging |
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| , , , , , , , , and , Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Convolutional Neural Networks, 2025 |
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| , , , , , , , , , , and , AI-based Prediction of Myocardium Viability Using [82Rb] PET/CT, 2025 |
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| , , , , , , , , , , , , and , A radiomics-based analysis of functional dopaminergic scintigraphic imaging for the diagnosis of dementia with Lewy bodies (2025), in: Neurodegenerative Diseases |
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| , , , , , , , and , Integrating MRI and PET/CT Radiomics for Enhanced Survival Prediction in Esophageal Cancer, in: European Congress of Radiology, 2025 |
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| , , , , , , , , , and , Lung lesion detectability on images obtained from decimated and CNN-based denoised [18F]-FDG PET/CT scan: An observer-based study for lung-cancer screening (2025), in: European Journal of Nuclear Medicine and Molecular Imaging |
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| , , , , , , and , Evaluation of PaIRe PET/CT segmentation software as cancerous lesion contouring tool in fully- automated annotation workflows for image-based research studies, in: Annual Congress of the European Association of Nuclear Medicine, 2023 |
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| , , , , , , , , , and , Lung lesion detectability on decimated and CNN-based denoised 18F-FDG PET/CT, in: Swiss Congress of Radiology, 2024 |
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| , , , , , and , Design implications of repurposing a radiomics research platform for education: The case of QuantImage v2, 2024 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT, páginas 1-30, Springer, Cham, 2023 |
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| , , , and , Guide for radiologists and nuclear medicine physicians for a standardized radiomics analysis, in: Swiss Congress of Radiology (SCR) 2023, 2023 |
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| , , , , , , and , HEad and neCK TumOR segmentation and outcome prediction using AI: lessons from three consecutive years of the HECKTOR challenge, in: European Head and Neck Society (EHNS) on Artificial Intelligence (AI) in Head & Neck Oncology, Lausanne and virtual, 2023 |
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, , , , , , , , , , and , Automatic Head and Neck Tumor Segmentation and Outcome Prediction Relying on FDG-PET/CT Images: Findings from the Second Edition of the HECKTOR Challenge (2023), in: Medical Image Analysis, 90:1(102972)
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, , , , , and , Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT (2022), in: European Journal of Hybrid Imaging, 6:1(33)
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| , , , , , , , and , HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022 |
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| , , , , , and , Reproducibility of lung cancer radiomic features extracted from data-driven respiratory gating and free-breathing flow imaging in 18F-FDG PET/CT, in: 2022 Annual Meeting of the Society of Nuclear Medicine and Molecular Imaging (SNMMI), 2022 |
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| , , , , , , , , , and , Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images, in: Head and Neck Tumor Segmentation and Outcome Prediction, páginas 1-37, 2022 |
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| , , , , and , Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT, in: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), páginas 4731-4735, 2022 |
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, , , , , , , , , and , Cleaning Radiotherapy Contours for Radiomics Studies, is it Worth it? A Head and Neck Cancer Study (2022), in: Clinical and Translational Radiation Oncology, 33(153-158)
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, , , , , , , , and , QuantImage v2: A Comprehensive and Integrated Physician-Centered Cloud Platform for Radiomics and Machine Learning Research (2023), in: European Radiology Experimental, 7:16
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| , , , , , , , and , QuantImage v2: A Clinician-in-the-loop Cloud Platform for Radiomics Research, in: European Society of Radiology, 2022 |
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, , , , , , , , , , , , , , , , , , , , , , , , , and , Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)
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| , , , , , and , Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer, in: 4th Workshop on PRedictive Intelligence in MEdicine, páginas 147-156, Springer LNCS, 2021 |
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| , , , , , and , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, páginas 59-68, Springer LNCS, 2021 |
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| , , , , , , and , Rethinking the Role of AI with Physicians in Oncology: Revealing Perspectives from Clinical and Research Workflows, in: ACM CHI 2023, 2023 |
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| , , , , , , and , Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT, páginas 1-21, 2021 |
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| , , , , , , and , Impact of a Gaussian filter applied to post-reconstruction PET on radiomic features in assessing tumor heterogeneity in breast cancer. (2020), in: Journal of Nuclear Medicine, 61:supplement 1(612--612) |
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| , , , , and , PET/CT Radiomics predict Pulmonary Lymphangitic Carcinomatosis (PLC) in Non-Small Cell Lung Cancer (NSCLC) (2020), in: Journal of Nuclear Medicine, 61:supplement 1(1311--1311) |
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| , , , , , , and , Impact of a Gaussian filter applied to post-reconstruction PET images on radiomic features to predict complete pathological response in breast cancer (2020), in: Journal of Nuclear Medicine, 61:supplement 1(606--606) |
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| , , , , , , , and , Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans, in: Medical Imaging with Deep Learning, Montréal, Canada, 2020 |
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| , , and , PET/CT Radiomics Analysis Contributes to Detection of Pulmonary Lymphangitic Carcinomatosis (PLC) in Non-Small Cell Lung Cancer (NSCLC), in: Swiss Congress of Radiology, 2019 |
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, , , , , , , and , Signature of Survival: A 18F-FDG PET Based Whole-Liver Radiomics Analysis Predicts Survival After 90Y-TARE for Hepatocellular Carcinoma (2017), in: OncoTarget, 9:4(4549-4558)
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