Advancing modified barium swallow pre-sorting with deep learning: a new paradigm for the first step analysis in X-ray swallowing study
Our analysis highlighted the importance of leveraging inter-frame connectivity for improving the model performance. These findings significantly boost MBS exam processing efficiency, minimizing manual sorting efforts and allowing raters to allocate greater focus to clinical interpretation and patient care.
Authors
- Kristy K. Brock (ORCID: https://orcid.org/0000-0001-9364-5040)
- Shitong Mao (ORCID: https://orcid.org/0000-0002-5122-7497)
- Katherine A. Hutcheson (ORCID: https://orcid.org/0000-0003-3710-5706)
- Sheila Buoy
- Mohamed A. Naser (ORCID: https://orcid.org/0000-0003-1020-4966)
Institutions
- The University of Texas MD Anderson Cancer Center (US)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2025-10-04
- DOI
- https://doi.org/10.1007/s11548-025-03505-y
- Primary Topic
- Dysphagia Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Emory University
- National Institutes of Health
- University of Texas MD Anderson Cancer Center
- National Cancer Institute