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Found 5 papers, 2 papers with code
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
The test dataset will be used for model validation only and will not be released to the public.
An augmentation strategy to mimic multi-scanner variability in MRI
Most publicly available brain MRI datasets are very homogeneous in terms of scanner and protocols, and it is difficult for models that learn from such data to generalize to multi-center and multi-scanner data.
Improved inter-scanner MS lesion segmentation by adversarial training on longitudinal data
A discriminator model is then trained to predict if two lesion segmentations are based on scans acquired using the same scanner type or not, achieving a 78% accuracy in this task.
Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors
In this work, we explore a novel approach to harmonize brain volume measurements by using only image descriptors.
Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis
Specifically, we apply the \emph{shades of gray} color constancy technique to color-normalize the entire training set of images, while retaining the estimated illuminants.
