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niimath and fslmaths: replication as a method to enhance popular neuroimaging tools

Journal article

Rorden C. et al, (2024), Aperture Neuro, 4

BIANCA-MS: An optimized tool for automated multiple sclerosis lesion segmentation.

Journal article

Gentile G. et al, (2023), Hum Brain Mapp

Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria

Journal article

Bozek J. et al, (2023), NeuroImage, 119864 - 119864

STAMP: Simultaneous Training and Model Pruning for low data regimes in medical image segmentation

Journal article

Dinsdale NK. et al, (2022), Medical Image Analysis, 102583 - 102583

How certain are your uncertainties?

Preprint

Whitbread L. and Jenkinson M., (2022)

Uncertainty Categories in Medical Image Segmentation: A Study of Source-Related Diversity

Chapter

Whitbread L. and Jenkinson M., (2022), Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 26 - 35

Brain Tumour Segmentation Using a Triplanar Ensemble of U-Nets on MR Images

Chapter

Sundaresan V. et al, (2021), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 340 - 353

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