11 citations · 18 across the 2 of their papers we have counts for
3 papers
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…
Model-Informed Machine Learning for Multi-component T2 Relaxometry
Thomas Yu, Erick Jorge Canales Rodriguez, Marco Pizzolato +9
Recovering the T2 distribution from multi-echo T2 magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-st…
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…