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09/07/2023
Social Media Influence Operations
Social media platforms enable largely unrestricted many-to-many communic...
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01/02/2021
Combining unsupervised and supervised learning for predicting the final stroke lesion
Predicting the final ischaemic stroke lesion provides crucial informatio...
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12/11/2020
Uncertainty-driven refinement of tumor-core segmentation using 3D-to-2D networks with label uncertainty
The BraTS dataset contains a mixture of high-grade and low-grade gliomas...
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04/04/2019
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks
In applications of supervised learning applied to medical image segmenta...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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09/25/2018
Automatic brain tumor grading from MRI data using convolutional neural networks and quality assessment
Glioblastoma Multiforme is a high grade, very aggressive, brain tumor, w...
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06/12/2018
Enhancing clinical MRI Perfusion maps with data-driven maps of complementary nature for lesion outcome prediction
Stroke is the second most common cause of death in developed countries, ...
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06/11/2018
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning
In this work, we present a novel convolutional neural net- work based me...
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06/08/2018
Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation
Uncertainty estimates of modern neuronal networks provide additional inf...
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06/07/2018
On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation
Uncertainty estimation methods are expected to improve the understanding...
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03/01/2017