Detecting Six Different Types of Thyroid Diseases Using Deep Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-7018-3_5
Reference10 articles.
1. Zhou H, Wang K, Tian J (2020) Online transfer learning for differential diagnosis of benign and malignant thyroid nodules with ultrasound images. IEEE Trans Biomed Eng 67(10)
2. Kumar V, Webb J, Gregory A, Meixner DD, Knudsen JM, Callstrom M, Fatemi M, Alizad A (2020) Automated segmentation of thyroid nodule, gland, and cystic components from ultrasound images using deep learning. IEEE
3. Song W, Li S, Liu J, Qin H, Zhang B, Zhang S, Hao A (2018) Multi-task cascade convolution neural networks for automatic thyroid nodule detection and recognition. IEEE J Biomed Health Inf
4. Rosen JE∗, Suh H, Giordano NJ, A’amar OM, Rodriguez-Diaz E, Bigio II, Lee SL (2016) Preoperative discrimination of benign from malignant disease in thyroid nodules with indeterminate cytology using elastic light-scattering spectroscopy. IEEE Trans Biomed Eng 61(8)
5. Anton-Rodriguez JM, Julyan P, Djoukhadar I, Russell D, Gareth Evans D, Jackson A, Matthews JC (2019) Comparison of a standard resolution PET-CT scanner with an HRRT brain scanner for imaging small tumors within the head. IEEE Trans Radiat Plasma Med Sci 3(4)
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