Advanced kidney mass segmentation using VHUCS-Net with protuberance detection network
These results indicate improved diagnostic efficiency and support clinical decision making by providing more accurate and interpretable segmentation outputs. Moreover, VHUCS-Net is validated with additional publicly available datasets with image mask correspondence, therefore proving the model effectiveness and generalizability across many segmentation tasks. The results highlight the capability of the proposed VHUCS-Net model to enhance diagnostic accuracy and assist clinical decision making through more detailed and interpretable segmentation outcomes.
Authors
- J. Jenifa Sharon
- L. Jani Anbarasi
Institutions
- Vellore Institute of Technology University (IN)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2026-02-04
- DOI
- https://doi.org/10.3389/frai.2026.1716063
- Citations
- 1
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 46.84