Exploring Multi-Pathology Brain Segmentation: From Volume-Based to Component-Based Deep Learning Analysis
Detection and segmentation of brain abnormalities using Magnetic Resonance Imaging (MRI) is an important task that, nowadays, the role of AI algorithms as supporting tools is well established both at the research and clinical-production level. While the performance of the state-of-the-art models is...
Saved in:
Main Authors: | Ioannis Stathopoulos, Roman Stoklasa, Maria Anthi Kouri, Georgios Velonakis, Efstratios Karavasilis, Efstathios Efstathopoulos, Luigi Serio |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/11/1/6 |
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) -
Examining vaccination-related adverse events in frequent neurodegenerative diseases
by: Shabnam Sodagari, et al.
Published: (2025-02-01) -
Magnetic Resonance Imaging Techniques for Post-Treatment Evaluation After External Beam Radiation Therapy of Prostate Cancer: Narrative Review
by: Eleni Bekou, et al.
Published: (2024-12-01) -
Cognitive Impairment and Fall Risk in Multiple Sclerosis: A Review Study
by: Negar Balali, et al.
Published: (2025-03-01)