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Nataliia Molchanova

Showing results (1-10 of 7) with videos related to

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Human Brain Mapping|June 20, 2024
Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistencyNataliia Molchanova, Bénédicte Maréchal, Jean-Philippe Thiran, et al.
Neuroimage. Clinical|July 22, 2025
Fluid and White Matter Suppression contrasts MRI improves Deep Learning detection of Multiple Sclerosis Cortical LesionsPedro M Gordaliza, Jannis Müller, Alessandro Cagol, et al.
Scientific Reports|February 1, 2026
Instance-level quantitative saliency in multiple sclerosis lesion segmentationFederico Spagnolo, Nataliia Molchanova, Meritxell Bach Cuadra, et al.
Computers in Biology and Medicine|November 15, 2024
Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentationNataliia Molchanova, Vatsal Raina, Andrey Malinin, 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.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Human Brain Mapping|June 20, 2024
Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistencyNataliia Molchanova, Bénédicte Maréchal, Jean-Philippe Thiran, et al.
Neuroimage. Clinical|July 22, 2025
Fluid and White Matter Suppression contrasts MRI improves Deep Learning detection of Multiple Sclerosis Cortical LesionsPedro M Gordaliza, Jannis Müller, Alessandro Cagol, et al.
Scientific Reports|February 1, 2026
Instance-level quantitative saliency in multiple sclerosis lesion segmentationFederico Spagnolo, Nataliia Molchanova, Meritxell Bach Cuadra, et al.
Computers in Biology and Medicine|November 15, 2024
Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentationNataliia Molchanova, Vatsal Raina, Andrey Malinin, 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.
Pageof 1