A Case for Automated Segmentation of MRI Data in Neurodegenerative Diseases: Type II GM1 Gangliosidosis
Previous studies have considered automated segmentation techniques to be unreliable, particularly in neurodegenerative diseases. However, in our study, we produced results comparable to those obtained with a manual segmentation process. While manual segmentation processes conducted by neuroradiologists remain the gold standard, we present evidence to the capabilities and advantages of using an automated process that includes the ability to segment white matter throughout the brain or analyze large datasets, which pose feasibility issues to fully manual processes. Future investigations should consider the use of artificial intelligence-based segmentation pipelines to determine their accuracy in GM1 gangliosidosis, lysosomal storage disorders, and other neurodegenerative diseases.
Authors
- Muhammad Yousef
- Maria T. Acosta (ORCID: https://orcid.org/0000-0001-8914-7401)
- Mohammed Salman Shazeeb (ORCID: https://orcid.org/0000-0002-3175-8098)
- Jean M. Johnston
- Cynthia J. Tifft (ORCID: https://orcid.org/0000-0002-3931-1207)
- Anna Luisa Kühn (ORCID: https://orcid.org/0000-0001-9512-9461)
- Christopher Zoppo (ORCID: https://orcid.org/0000-0002-1697-7735)
- Connor Lewis (ORCID: https://orcid.org/0000-0002-8204-5848)
- Josephine Kolstad
- William A. Gahl (ORCID: https://orcid.org/0000-0002-2494-6752)
- Zubir Rentiya (ORCID: https://orcid.org/0000-0002-5838-0806)
- Ahmet Peker (ORCID: https://orcid.org/0000-0002-4913-6860)
- Zeynep Vardar (ORCID: https://orcid.org/0000-0002-7510-9524)
- Precilla D’Souza (ORCID: https://orcid.org/0009-0007-0395-1011)
Institutions
- Koç University (TR)
- University of Massachusetts Chan Medical School (US)
- McLean Hospital (US)
- National Human Genome Research Institute (US)
- National Institutes of Health Clinical Center (US)
- University of Virginia (US)
Publication Details
- Journal
- NeuroSci
- Published
- 2025-04-03
- DOI
- https://doi.org/10.3390/neurosci6020031
- Citations
- 4
- Primary Topic
- Lysosomal Storage Disorders Research
- Type
- article
- Field-Weighted Citation Impact
- 4.66
Funders
- National Institutes of Health