Nicola K. Dinsdale
According to our database1,
Nicola K. Dinsdale
authored at least 19 papers
between 2019 and 2024.
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Bibliography
2024
Anatomically plausible segmentations: Explicitly preserving topology through prior deformations.
Medical Image Anal., 2024
Automated quality assessment using appearance-based simulations and hippocampus segmentation on low-field paediatric brain MR images.
CoRR, 2024
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos.
CoRR, 2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
2022
STAMP: Simultaneous Training and Model Pruning for low data regimes in medical image segmentation.
Medical Image Anal., 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Omni-Supervised Domain Adversarial Training for White Matter Hyperintensity Segmentation in the UK Biobank.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
2021
Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal.
NeuroImage, 2021
NeuroImage, 2021
Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images.
Medical Image Anal., 2021
CoRR, 2021
TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
Proceedings of the Medical Image Understanding and Analysis - 24th Annual Conference, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
A 2-Step Deep Learning Method with Domain Adaptation for Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Magnetic Resonance Segmentation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020
2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019