Schlagworte:
Publikationen von Cristina Granziera
2026
| , , , , , , , , , , , , und , A multi-modal deep learning network for the classification of paramagnetic rim and remyelinated lesions in multiple sclerosis (2026), in: Multiple Sclerosis Journal |
| , , , , , , , und , Instance-level quantitative saliency in multiple sclerosis lesion segmentation (2026), in: Nature Scientific Reports |
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2025
| , , , , , , , , , , und , Deep-PRL: a deep learning network for the identification of paramagnetic rim lesions in multiple sclerosis, in: ISMRM 2025, 2025 |
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| , , , , , , , , , , , , , , , und , Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors, 2025 |
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| , , , , , , und , Exploiting XAI maps to improve MS lesion segmentation and detection in MRI, in: Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI, 2025 |
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| , , , , , , , , und , Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation (2025), in: Computers in Biology and Medicine |
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2024
| , , , , , , , und , Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study (2024), in: Frontiers in Neuroimaging, 3 |
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| , , , , , , , , , , , und , Explainability in automatic Paramagnetic Rim Lesion classification, in: 40th Congress Of The European Committee For Treatment And Research In Multiple Sclerosis (ECTRIMS), 2024 |
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| , , , , , , , und , Instance-level explanations in multiple sclerosis lesion segmentation: a novel localized saliency map, in: ISMRM 2024, 2024 |
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| , , , , , , , , , und , Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis, 2024 |
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| , , , , , , , und , Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling, 2024 |
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2023
| , , , , , , , und , Deep learning uncertainty quantification of cortical lesions in MP2RAGE for missed lesions discovery, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
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| , , , , , , , und , FLAIR vs MPRAGE contribution to white matter lesion automatic segmentation in MS using localized saliency maps, in: Bern Interpretable AI Symposium (BIAS), 2023 |
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| , , , , , , und , FLAWS against flaws: Improving Automated Cortical Lesion Segmentation, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
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, , , , , , und , How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review (2023), in: NeuroImage: Clinical, 39(103491)
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , Identification of paramagnetic rim lesions using conventional MRI - a deep learning approach, in: 39th Congress Of The European Committee For Treatment And Research In Multiple Sclerosis (ECTRIMS), 2023 |
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| , , , , , , , und , NOVEL STRUCTURAL-SCALE UNCERTAINTY MEASURES AND ERROR RETENTION CURVES: APPLICATION TO MULTIPLE SCLEROSIS (2023), in: Proceedings of International Symposium of Biomedical Imaging 2023 |
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| , , , , , , , , , , , , , und , Streamline RimNet: A Deep Learning Classification of Paramagnetic Rim Lesions, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
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| , , , , , , , , und , The Normalised Dice Similarity Coefficient for MS: tackling lesion load biases in white matter and cortical lesion segmentation, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
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| , , , , , , , und , Towards Informative Uncertainty Measures for MRI Segmentation in Clinical Practice: Application to Multiple Sclerosis, ISMRM & ISMRT 2023 Annual Meeting & Exhibition, 2023 |
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| , , , , , , , und , Towards Informative Uncertainty Measures for MRI Segmentation in Clinical Practice: Application to Multiple Sclerosis, in: Bern Interpretable Symposium (BIAS) 2023, 2023 |
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2022
| , , , , , , , , , , , , , , , , und , Shifts 2.0: Extending The Dataset of Real Distributional Shifts, arXiv, 2022 |
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