3 papers
cs.CV2020
Disentangling Human Error from the Ground Truth in Segmentation of Medical Images
Le Zhang, Ryutaro Tanno, Mou-Cheng Xu +5
Recent years have seen increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depends on the quality of label…
physics.med-ph2019
Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination
Ioana Hill, Marco Palombo, Mathieu Santin +14
The intra-axonal water exchange time τi, a parameter associated with axonal permeability, could be an important biomarker for understanding demyelinating pathologies such as Multip…
cs.CV2018
Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks
Charley Gros, Benjamin De Leener, Atef Badji +49
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of…