Publications of Nataliia Molchanova sorted by first author
G
| , , , , , , , and , Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling, 2024 |
[DOI] |
| , , , , , , and , FLAWS against flaws: Improving Automated Cortical Lesion Segmentation, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
|
M
| , , , , , , , , , , , , , , , , and , Shifts 2.0: Extending The Dataset of Real Distributional Shifts, arXiv, 2022 |
[DOI] [URL] |
| , , , , , , , and , 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 |
|
| , , , , , , , , , and , Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis, 2024 |
|
| , , , , and , Fast refacing of MR images with a generative neural network lowers re‐identification risk and preserves volumetric consistency (2024), in: Human Brain Mapping, 45:9 |
[DOI] [URL] |
| , , , , , , , and , Towards Informative Uncertainty Measures for MRI Segmentation in Clinical Practice: Application to Multiple Sclerosis, ISMRM & ISMRT 2023 Annual Meeting & Exhibition, 2023 |
|
| , , , , , , , and , Towards Informative Uncertainty Measures for MRI Segmentation in Clinical Practice: Application to Multiple Sclerosis, in: Bern Interpretable Symposium (BIAS) 2023, 2023 |
|
| , , , , , , , , and , Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation (2025), in: Computers in Biology and Medicine |
[DOI] |
| , , , , , , , and , NOVEL STRUCTURAL-SCALE UNCERTAINTY MEASURES AND ERROR RETENTION CURVES: APPLICATION TO MULTIPLE SCLEROSIS (2023), in: Proceedings of International Symposium of Biomedical Imaging 2023 |
|
N
| , , , , , , , , , , , , , and , Streamline RimNet: A Deep Learning Classification of Paramagnetic Rim Lesions, European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) Conference 2023, 2023 |
|
S
| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , 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 |
|
| , , , , , , and , 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, 2024 |
|
| , , , , , , , and , Instance-level quantitative saliency in multiple sclerosis lesion segmentation (2024), in: arxiv |
[URL] |
| , , , , , , , and , Instance-level explanations in multiple sclerosis lesion segmentation: a novel localized saliency map, in: ISMRM 2024, 2024 |
| , , , , , , , and , FLAIR vs MPRAGE contribution to white matter lesion automatic segmentation in MS using localized saliency maps, in: Bern Interpretable AI Symposium (BIAS), 2023 |
|
V
| , , , , , , , , and , 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 |
|
| , , , , , and , Tackling Bias in the Dice Similarity Coefficient: Introducing nDSC for White Matter Lesion Segmentation, in: IEEE International Symposium on Biomedical Imaging, 2023 |
|