Intelligent segmentation of thyroid nodule ultrasound images based on benign-malignant-aware semantic prototype calibration and class-conditional boundary refinement.

Luo B, Li R, Tang Y

Open source

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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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

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