Specialized gray matter segmentation via a generative adversarial network: application on brain white matter hyperintensities classification
After training, the method proves its efficiency by providing results in less than one second. In contrast, the usual approach would require at least two minutes for registration and segmentation alone. The proposed method is automated and fast and requires no initialization as it works exclusively with FLAIR images. Such innovative methods will undoubtedly facilitate accurate and meaningful analysis of WMH in clinical practice by reducing complexity and increasing efficiency.
Authors
- Mousa Shamsi (ORCID: https://orcid.org/0000-0003-4670-0531)
- Sebelan Danishvar (ORCID: https://orcid.org/0000-0002-8258-0437)
- Abolhassan Shakeri Bavil (ORCID: https://orcid.org/0000-0001-9397-0484)
- Mahdi Bashiri Bawil
Institutions
- Sahand University of Technology (IR)
- Tabriz University of Medical Sciences (IR)
- Brunel University of London (GB)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2024-09-30
- DOI
- https://doi.org/10.3389/fnins.2024.1416174
- Citations
- 4
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.00