Enhanced thyroid nodule detection and diagnosis: a mobile-optimized DeepLabV3+ approach for clinical deployments
DeepLabV3+ represents a significant advancement in thyroid nodule segmentation, particularly for thyroid cancer screening and diagnosis. The obtained segmentation results suggest promising directions for future research, especially in the early detection of thyroid nodules. Deploying this algorithm on mobile devices offers a practical solution for early diagnosis and is likely to improve patient outcomes.
Authors
- Hongyuan Huang
- Mudassar Riaz (ORCID: https://orcid.org/0000-0003-4757-6595)
- Muhammad Awais Ashraf (ORCID: https://orcid.org/0000-0003-4085-8995)
- Changan Yang (ORCID: https://orcid.org/0000-0002-4365-6523)
- Kavimbi Chipusu
- Yueqin Xu (ORCID: https://orcid.org/0009-0002-6003-7238)
- Pascal Umwanzavugaye
Institutions
- Central South University (CN)
- Chang'an University (CN)
- University of Saskatchewan (CA)
- Shanghai Sixth People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-03-24
- DOI
- https://doi.org/10.3389/fphys.2025.1457197
- Citations
- 4
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 5.18