A multi-task model for reliable classification of thyroid nodules in ultrasound images
Author:
Funder
Foundation of Equipment Pre-research Area
Key Technologies Research and Development Program
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s13534-023-00325-4.pdf
Reference36 articles.
1. Zhang J, Zhang F, Zhao C, Xu Q, Liang C, Yang Y, et al. Dysbiosis of the gut microbiome is associated with thyroid cancer and thyroid nodules and correlated with clinical index of thyroid function. Endocrine. 2019;64(3):564–74. https://doi.org/10.1007/s12020-018-1831-x.
2. Meiburger KM, Acharya UR, Molinari F. Automated localization and segmentation techniques for B-mode ultrasound images: a review. Comput Biol Med. 2018;92:210–35. https://doi.org/10.1016/j.compbiomed.2017.11.018.
3. Tessler FN, Middleton WD, Grant EG, Hoang JK, Berland LL, Teefey SA, et al. ACR thyroid imaging, reporting and data system (TI-RADS): white paper of the ACR TI-RADS committee. J Am Coll Radiol. 2017;14(5):587–95. https://doi.org/10.1016/j.jacr.2017.01.046.
4. Park JY, Lee HJ, Jang HW, Kim HK, Yi JH, Lee W, et al. A proposal for a thyroid imaging reporting and data system for ultrasound features of thyroid carcinoma. Thyroid. 2009;19(11):1257–64. https://doi.org/10.1089/thy.2008.0021.
5. Hoang JK, Middleton WD, Farjat AE, Langer JE, Reading CC, Teefey SA, et al. Reduction in thyroid nodule biopsies and improved accuracy with American College of Radiology Thyroid Imaging Reporting and Data System. Radiology. 2018;287(1):185–93. https://doi.org/10.1148/radiol.2018172572.
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