Trefwoorden:
Publicaties van Stephanie Tanadini-Lang gesorteerd op nieuwheid
| , , , , , , , , , , , , en , Deep learning [18F]-FDG-PET/CT‑based algorithm for tumor burden estimation in metastatic melanoma patients under immunotherapy (2025), in: Clinical and Translational Radiation Oncology |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , A Multimodal and Multi-centric Head and Neck Cancer Dataset for Tumor Segmentation and Outcome Prediction (2025) |
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, , , , , , , , , , , , , , , , , , , , en , The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information, 2025
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| , , , , , , , , , , , en , Deep learning PET/CT-based algorithm for estimating tumor burden in metastatic melanoma patients under immunotherapy, in: ESTRO 2025, 2025 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights (2024), in: Radiology, 310:2
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT, pagina's 1-30, Springer, Cham, 2023 |
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| , , , , , , , , , , , en , Impact of deep learning segmentation methods on the robustness of MR glioblastoma radiomics, in: 2022 Annual Meeting of the European Society of Radiation Oncology (ESTRO), 2022 |
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| , , , , , en , Deep learning classifier for MGMT promoter methylation status in glioblastoma cancer, in: 2022 Annual Meeting of the European Society of Radiation Oncology (ESTRO), 2022 |
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| , , , , , , , en , Comparison of MR preprocessing strategies and sequences for radiomics-based MGMT prediction, in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (MICCAI/BrainLes 2021), Cham, pagina's 367–380, Springer International Publishing, 2022 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , en , Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)
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