Editorial: Deep learning and neuroimage processing in understanding neurological diseases
2024
Deep Learning and Neuroimage Processing in Understanding Neurological Diseases
Editorial
Author Information
Author(s): Joana Carvalho, Ali Abdollahzadeh, Ricardo José Ferrari
Conclusion
Recent advancements in deep learning have significantly improved the analysis and diagnosis of neurological diseases through enhanced neuroimaging techniques.
Supporting Evidence
- Deep learning algorithms excel in tasks like brain segmentation and lesion detection.
- Challenges in neuroimaging include data variability and poor generalizability across modalities.
- Recent advancements have improved the accuracy of brain segmentation and cohort classification.
Takeaway
This study shows how computers can help doctors understand brain images better, making it easier to find and treat brain problems.
Potential Biases
Potential bias in AI models due to reliance on specific datasets.
Limitations
Challenges include data variability, quality issues, and limited training on pathological cases.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website