Toward Generalizable Multiple Sclerosis Lesion Segmentation Models
Automating Multiple Sclerosis (MS) lesion segmentation would be of great benefit in initial diagnosis as well as monitoring disease progression. Deep learning based segmentation models perform well in many domains, but the state-of-the-art in MS lesion segmentation is still suboptimal. Complementary...
Saved in:
| Main Authors: | Liviu Badea, Maria Popa |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11021622/ |
| 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) -
SARS‐CoV‐2 Is Linked to Brain Volume Loss in Multiple Sclerosis
by: Tomas Uher, et al.
Published: (2025-08-01) -
Overtime Challenges of Diagnosis and Treatment in Two Pediatric Patients with Extensive Cerebral Tumefactive Lesions Indicative of Baló’s Type Multiple Sclerosis
by: Alice Denisa Dică, et al.
Published: (2025-05-01) -
AI-Assisted MRI Analysis for Multiple Sclerosis: Lesion Detection and Brain Atrophy Assessment
by: Ioana-Andreea CÎRLIG, et al.
Published: (2025-05-01) -
Determinants driving the evolution of new multiple sclerosis lesions into chronic active or remyelinated states
by: G. Boffa, et al.
Published: (2025-01-01)