Intelligent segmentation of thyroid nodule ultrasound images based on benign-malignant-aware semantic prototype calibration and class-conditional boundary refinement.
- DOI
- 10.3389/fcell.2026.1879094
- Published
- 2026
- Container
- Frontiers in cell and developmental biology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fcell.2026.1879094,
title = {Intelligent segmentation of thyroid nodule ultrasound images based on benign-malignant-aware semantic prototype calibration and class-conditional boundary refinement.},
author = {Luo B and Li R and Tang Y},
year = {2026},
journal = {Frontiers in cell and developmental biology},
doi = {10.3389/fcell.2026.1879094},
url = {https://doi.org/10.3389/fcell.2026.1879094}
}RIS
TY - JOUR TI - Intelligent segmentation of thyroid nodule ultrasound images based on benign-malignant-aware semantic prototype calibration and class-conditional boundary refinement. AU - Luo B AU - Li R AU - Tang Y PY - 2026 JO - Frontiers in cell and developmental biology DO - 10.3389/fcell.2026.1879094 UR - https://doi.org/10.3389/fcell.2026.1879094 ER -
APA
B, L., R, L., & Y, T. (2026). Intelligent segmentation of thyroid nodule ultrasound images based on benign-malignant-aware semantic prototype calibration and class-conditional boundary refinement.. Frontiers in cell and developmental biology. https://doi.org/10.3389/fcell.2026.1879094
Source records
- pubmed · retrieved 2026-09-25T01:48:35.548Z