PreprintAll rights reservedmedRxiv
Bridging field strengths: fine-tuned deep learning models for 7T MRI white matter lesion segmentation in multiple sclerosis
- 1McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Can
Related
- Multi-scale Gaussian product-of-experts for missing sequence multiple sclerosis lesion segmentation
- Regularization via gradient attribution for multiple sclerosis lesion segmentation.
- Automated optic chiasm segmentation in magnetic resonance imaging of multiple sclerosis patients using a multi-view, multi-class U-Net with limited annotated data
- A Feasible Machine Learning Approach to Improve Cognitive Screening in Multiple Sclerosis
- Prospective validation of an uncertainty-aware machine learning model for secondary progressive multiple sclerosis classification
BibTeX
@misc{rosa2026bridging,
title = {{Bridging field strengths: fine-tuned deep learning models for 7T MRI white matter lesion segmentation in multiple sclerosis}},
author = {A. P. De Rosa and H.-E. Assemlal and D. Fetco and D. Araujo and M. K. Schindler and E. S. Beck and R. Bakshi and D. S. Reich and D. M. Harrison and F. Esposito and D. A. Rudko and D. L. Arnolde and S. Narayanan},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.03.26362180},
url = {https://www.medrxiv.org/content/10.64898/2026.09.03.26362180v1},
}
RIS
TY - UNPB
TI - Bridging field strengths: fine-tuned deep learning models for 7T MRI white matter lesion segmentation in multiple sclerosis
AU - A. P. De Rosa
AU - H.-E. Assemlal
AU - D. Fetco
AU - D. Araujo
AU - M. K. Schindler
AU - E. S. Beck
AU - R. Bakshi
AU - D. S. Reich
AU - D. M. Harrison
AU - F. Esposito
AU - D. A. Rudko
AU - D. L. Arnolde
AU - S. Narayanan
PY - 2026
DA - 2026/09/03
PB - medRxiv
DO - 10.64898/2026.09.03.26362180
UR - https://www.medrxiv.org/content/10.64898/2026.09.03.26362180v1
ER -