Quantitative Super-Resolution Ultrasound Microvascular Features for Machine Learning-Based Classification of Thyroid Nodules.

Tian Y, Wang Y, Chen N, Xu R, Liu Y, Wang Z.

DOI: 10.3791/72803
Published: 2026-09-11
Container: J Vis Exp
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.3791/72803,
  title = {Quantitative Super-Resolution Ultrasound Microvascular Features for Machine Learning-Based Classification of Thyroid Nodules.},
  author = {Tian Y and  Wang Y and  Chen N and  Xu R and  Liu Y and  Wang Z.},
  year = {2026},
  journal = {J Vis Exp},
  doi = {10.3791/72803},
  url = {https://doi.org/10.3791/72803}
}

RIS

TY  - JOUR
TI  - Quantitative Super-Resolution Ultrasound Microvascular Features for Machine Learning-Based Classification of Thyroid Nodules.
AU  - Tian Y
AU  -  Wang Y
AU  -  Chen N
AU  -  Xu R
AU  -  Liu Y
AU  -  Wang Z.
PY  - 2026
JO  - J Vis Exp
DO  - 10.3791/72803
UR  - https://doi.org/10.3791/72803
ER  -

APA

Y, T., Y, W., N, C., R, X., Y, L., & Z., W. (2026). Quantitative Super-Resolution Ultrasound Microvascular Features for Machine Learning-Based Classification of Thyroid Nodules.. J Vis Exp. https://doi.org/10.3791/72803

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europe-pmc · retrieved 2026-09-25T07:55:39.204Z