MedGIFT
Topic: SPHN QA4IQI
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SPHN/PHRT infrastructure project Subtopics: Keywords: |
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Publications for topic "SPHN QA4IQI"
2023
, , , , , , , and , 3D-Printed Iodine-Ink CT Phantom for Radiomics Feature Extraction - Advantages and Challenges (2023), in: Medical Physics, 50:9(5682-5697)
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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 , 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 , 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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2022
, , , , , , , , and , Assessing radiomics feature stability with simulated CT acquisitions (2022), in: Scientific Reports, 12:1(4732)
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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 , Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)
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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, pages 1-37, 2022 |
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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 , The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022 |
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2021
| , , , , , , , , and , Assessment of the stability and discriminative power of radiomics features in liver lesions using an anthropomorphic 3D-printed CT phantom, in: Scientific session SGR-SSR, 2021 |
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| , , , , , and , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pages 59-68, Springer LNCS, 2021 |
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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, pages 147-156, Springer LNCS, 2021 |
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| , , , , , , and , Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT, pages 1-21, 2021 |
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| , , , and , QuantImage v2: an Open-Source and Web-Based Integrated Platform for Clinical Radiomics Research, in: Joint scientific session SSRMP/SGR-SSR, 2021 |
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| , , , , , , , , and , Revealing most suitable CT radiomics features for retrospective studies with heterogeneous datasets, in: European Congress of Radiology (ECR) 2021, ONLINE edition, 2021 |
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, , , , , , , , and , The discriminative power and stability of radiomics features with CT variations: Task-based analysis in an anthropomorphic 3D-printed CT phantom (2021), in: Investigative Radiology, 56:12(820-825)
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2020
, , , and , 3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis, 2020
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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 , Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)
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| , and , Oropharynx Detection in PET-CT for Tumor Segmentation, in: Irish Machine Vision and Image Processing Conference, 2020, 2020 |
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| , , , , , , and , Standardised convolutional filtering for radiomics, 2020 |
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, , , , and , The Importance of Feature Aggregation in Radiomics: A Head and Neck Cancer Study (2020), in: Nature Scientific Reports, 10:19679
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