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Adrien Depeursinge

Showing results (71-80 of 80) with videos related to

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Clinical and Translational Radiation Oncology|November 24, 2025
Deep learning [<sup>18</sup>F]-FDG-PET/CT‑based algorithm for tumor burden estimation in metastatic melanoma patients under immunotherapyLorenzo Lo Faro, Hubert S Gabryś, Simon Burgermeister, et al.
Artificial Intelligence Review|September 12, 2022
A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciencesMara Graziani, Lidia Dutkiewicz, Davide Calvaresi, et al.
Arxiv|July 30, 2025
Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction ErrorsNataliia Molchanova, Pedro M Gordaliza, Alessandro Cagol, et al.
Arxiv|September 19, 2025
Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple SclerosisNataliia Molchanova, Alessandro Cagol, Mario Ocampo-Pineda, et al.
Neuroimage. Clinical|June 1, 2026
A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosisNataliia Molchanova, Alessandro Cagol, Mario Ocampo-Pineda, et al.
Medical Image Analysis|January 11, 2022
Head and neck tumor segmentation in PET/CT: The HECKTOR challengeValentin Oreiller, Vincent Andrearczyk, Mario Jreige, et al.
Head and Neck Tumor Segmentation and Outcome Prediction : Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Head and Neck Tumor Segmentation Challenge (3Rd : 2022 : Singapor|May 17, 2023
Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CTVincent Andrearczyk, Valentin Oreiller, Moamen Abobakr, et al.
Radiology|February 6, 2024
The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical InsightsPhilip Whybra, Alex Zwanenburg, Vincent Andrearczyk, et al.
Radiology|March 11, 2020
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based PhenotypingAlex Zwanenburg, Martin Vallières, Mahmoud A Abdalah, et al.
Biomedizinische Technik. Biomedical Engineering|December 29, 2024
<i>MedShapeNet</i> - a large-scale dataset of 3D medical shapes for computer visionJianning Li, Zongwei Zhou, Jiancheng Yang, et al.
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Showing results (71-80 of 80) with videos related to

Sort By:
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You have reached the last page of results.This site can display upto 80 results.
Clinical and Translational Radiation Oncology|November 24, 2025
Deep learning [<sup>18</sup>F]-FDG-PET/CT‑based algorithm for tumor burden estimation in metastatic melanoma patients under immunotherapyLorenzo Lo Faro, Hubert S Gabryś, Simon Burgermeister, et al.
Artificial Intelligence Review|September 12, 2022
A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciencesMara Graziani, Lidia Dutkiewicz, Davide Calvaresi, et al.
Arxiv|July 30, 2025
Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction ErrorsNataliia Molchanova, Pedro M Gordaliza, Alessandro Cagol, et al.
Arxiv|September 19, 2025
Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple SclerosisNataliia Molchanova, Alessandro Cagol, Mario Ocampo-Pineda, et al.
Neuroimage. Clinical|June 1, 2026
A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosisNataliia Molchanova, Alessandro Cagol, Mario Ocampo-Pineda, et al.
Medical Image Analysis|January 11, 2022
Head and neck tumor segmentation in PET/CT: The HECKTOR challengeValentin Oreiller, Vincent Andrearczyk, Mario Jreige, et al.
Head and Neck Tumor Segmentation and Outcome Prediction : Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Head and Neck Tumor Segmentation Challenge (3Rd : 2022 : Singapor|May 17, 2023
Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CTVincent Andrearczyk, Valentin Oreiller, Moamen Abobakr, et al.
Radiology|February 6, 2024
The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical InsightsPhilip Whybra, Alex Zwanenburg, Vincent Andrearczyk, et al.
Radiology|March 11, 2020
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based PhenotypingAlex Zwanenburg, Martin Vallières, Mahmoud A Abdalah, et al.
Biomedizinische Technik. Biomedical Engineering|December 29, 2024
<i>MedShapeNet</i> - a large-scale dataset of 3D medical shapes for computer visionJianning Li, Zongwei Zhou, Jiancheng Yang, et al.
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