127 results on '"Oreiller, Valentin"'
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2. Why is the winner the best?
3. Biomedical image analysis competitions: The state of current participation practice
4. Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images
5. Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT
6. QuantImage v2: a comprehensive and integrated physician-centered cloud platform for radiomics and machine learning research
7. 3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis
8. Local Rotation Invariance in 3D CNNs
9. Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge
10. Comparison of MR Preprocessing Strategies and Sequences for Radiomics-Based MGMT Prediction
11. Wide kernels and their DCT compression in convolutional networks for nuclei segmentation
12. Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT
13. Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT
14. Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study
15. Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT
16. Multi-task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer
17. Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images
18. Comparison of MR Preprocessing Strategies and Sequences for Radiomics-Based MGMT Prediction
19. Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT
20. Multi-task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer
21. Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT
22. QuantImage v2: a comprehensive and integrated physician-centered cloud platform for radiomics and machine learning research
23. Wide Kernels and Their Dct Compression in Convolutional Networks for Nuclei Segmentation
24. Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients
25. Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT
26. Validating and optimizing the specificity of imaging biomarkers for personalized medicine
27. Head and neck tumor segmentation in PET/CT: The HECKTOR challenge
28. Self-supervised Multi-modality Image Feature Extraction for the Progression Free Survival Prediction in Head and Neck Cancer
29. Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images
30. Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT.
31. Local rotation invariance in 3D CNNs
32. Fusion-Based Automated Segmentation in Head and Neck Cancer via Advance Deep Learning Techniques
33. Combining nnUNet and AutoML for Automatic Head and Neck Tumor Segmentation and Recurrence-Free Survival Prediction in PET/CT Images
34. Towards Tumour Graph Learning for Survival Prediction in Head & Neck Cancer Patients
35. MLC at HECKTOR 2022: The Effect and Importance of Training Data When Analyzing Cases of Head and Neck Tumors Using Machine Learning
36. A Fine-Tuned 3D U-Net for Primary Tumor and Affected Lymph Nodes Segmentation in Fused Multimodal Images of Oropharyngeal Cancer
37. Recurrence-Free Survival Prediction Under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers
38. Stacking Feature Maps of Multi-scaled Medical Images in U-Net for 3D Head and Neck Tumor Segmentation
39. Octree Boundary Transfiner: Efficient Transformers for Tumor Segmentation Refinement
40. Head and Neck Primary Tumor and Lymph Node Auto-segmentation for PET/CT Scans
41. Automated Head and Neck Tumor Segmentation from 3D PET/CT HECKTOR 2022 Challenge Report
42. A General Web-Based Platform for Automatic Delineation of Head and Neck Gross Tumor Volumes in PET/CT Images
43. A Coarse-to-Fine Ensembling Framework for Head and Neck Tumor and Lymph Segmentation in CT and PET Images
44. HNT-AI: An Automatic Segmentation Framework for Head and Neck Primary Tumors and Lymph Nodes in FDG- PET/CT Images
45. Head and Neck Cancer Localization with Retina Unet for Automated Segmentation and Time-To-Event Prognosis from PET/CT Images
46. Deep Learning and Machine Learning Techniques for Automated PET/CT Segmentation and Survival Prediction in Head and Neck Cancer
47. Head and Neck Tumor Segmentation with 3D UNet and Survival Prediction with Multiple Instance Neural Network
48. Joint nnU-Net and Radiomics Approaches for Segmentation and Prognosis of Head and Neck Cancers with PET/CT Images
49. Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation
50. Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer
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