18 citations · 35 across the 4 of their papers we have counts for
5 papers
Novel structural-scale uncertainty measures and error retention curves: application to multiple sclerosis
Nataliia Molchanova, Vatsal Raina, Andrey Malinin +6
This paper focuses on the uncertainty estimation for white matter lesions (WML) segmentation in magnetic resonance imaging (MRI). On one side, voxel-scale segmentation errors cause…
Shifts 2.0: Extending The Dataset of Real Distributional Shifts
Andrey Malinin, Andreas Athanasopoulos, Muhamed Barakovic +15
Distributional shift, or the mismatch between training and deployment data, is a significant obstacle to the usage of machine learning in high-stakes industrial applications, such…
Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: emerging machine learning techniques and future avenues
Francesco La Rosa, Maxence Wynen, Omar Al-Louzi +11
The current multiple sclerosis (MS) diagnostic criteria lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, c…
Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI
Francesco La Rosa, Erin S Beck, Ahmed Abdulkadir +4
The automated detection of cortical lesions (CLs) in patients with multiple sclerosis (MS) is a challenging task that, despite its clinical relevance, has received very little atte…
Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis
Francesco La Rosa, Mário João Fartaria, Tobias Kober +4
In this work, we present a comparison of a shallow and a deep learning architecture for the automated segmentation of white matter lesions in MR images of multiple sclerosis patien…