Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation

Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation

Segmentation of Multiple Sclerosis (MS) lesions from Magnetic Resonance Imaging (MRI) data presents a significant challenge due to the necessity for large volumes of training data and a sophisticated training process. Traditional MRI datasets often lack the extensive sample sizes required for effect...

Full description

Saved in:
Bibliographic Details
Main Authors: Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Neuroimage: Reports
Subjects:
Multiple sclerosis
U-Net
Multi-modal MRI
Segmentation
Lesion detection
Online Access:http://www.sciencedirect.com/science/article/pii/S2666956025000030
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items