Web: http://arxiv.org/abs/2206.08272

June 17, 2022, 1:13 a.m. | Reda Abdellah Kamraoui, Boris Mansencal, José V Manjon, Pierrick Coupé

cs.CV updates on arXiv.org arxiv.org

The detection of new multiple sclerosis (MS) lesions is an important marker
of the evolution of the disease. The applicability of learning-based methods
could automate this task efficiently. However, the lack of annotated
longitudinal data with new-appearing lesions is a limiting factor for the
training of robust and generalizing models. In this work, we describe a
deep-learning-based pipeline addressing the challenging task of detecting and
segmenting new MS lesions. First, we propose to use transfer-learning from a
model trained on …

arxiv deep deep learning detection learning

More from arxiv.org / cs.CV updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY