Textural analysis and artificial intelligence as decision support tools in the diagnosis of multiple sclerosis – a systematic review
IntroductionMagnetic resonance imaging (MRI) is conventionally used for the detection and diagnosis of multiple sclerosis (MS), often complemented by lumbar puncture—a highly invasive method—to validate the diagnosis. Additionally, MRI is periodically repeated to monitor disease progression and trea...
Saved in:
Main Authors: | Filip Orzan, Ştefania D. Iancu, Laura Dioşan, Zoltán Bálint |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
|
Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2024.1457420/full |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation
by: Oezdemir Cetin, et al.
Published: (2025-03-01) -
Perfusion MRI in automatic classification of multiple sclerosis lesion subtypes
by: Ehsan Homayouny, et al.
Published: (2022-06-01) -
Clinical Characteristics of Early-Onset and Late-Onset Multiple Sclerosis in Patients from Lithuania
by: Emilija Šlajūtė, et al.
Published: (2025-01-01) -
Coexistence of multiple sclerosis
and systemic lupus erythematosus – a case report
by: Maciej Dubaj, et al.
Published: (2024-01-01) -
From diagnosis to treatment: exploring the mechanisms underlying optic neuritis in multiple sclerosis
by: Bin Tong, et al.
Published: (2025-01-01)