Open Access
| Issue |
E3S Web Conf.
Volume 185, 2020
2020 International Conference on Energy, Environment and Bioengineering (ICEEB 2020)
|
|
|---|---|---|
| Article Number | 03021 | |
| Number of page(s) | 5 | |
| Section | Medical Biology and Medical Signal Processing | |
| DOI | https://doi.org/10.1051/e3sconf/202018503021 | |
| Published online | 01 September 2020 | |
- P. Gabriella,F. Francesco,R. Concetto,S. Sebastiano,V. Riccardo, Worldwide Increasing Incidence of Thyroid Cancer: Update on Epidemiology and Risk Factors, J. Cancer Epidemio, (2013) [Google Scholar]
- K. Gul, D. Ozdemir, B. Korukluoglu, Preoperative and postoperative evaluation of thyroid disease in patients undergoing surgical treatment of primary hyperparathyroidism, Endocr Pract, 16,7–13(2010). [CrossRef] [PubMed] [Google Scholar]
- X. Li, S. Zhang, Q. Zhang,et al.Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective,multicohort,diagnostic study,The Lancet Oncology, 20(2),193–201(2019) [CrossRef] [PubMed] [Google Scholar]
- L.Wang, S. J. Yang, S. Yang,et al. Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network,World Journal of Surgical Oncology, 17(1),12(2019) [CrossRef] [PubMed] [Google Scholar]
- Q. Guan, Y. Wang, J. Du, et al.Deep learning based classification of ultrasound images for thyroid nodules: a large scale of pilot study,Ann. Transl. Med, 7(2019). [Google Scholar]
- J. Song,Y.Chai, H. Masuoka,et al.Ultrasound image analysis using deep learning algorithm for the diagnosis of thyroid nodules,Medicine, 98(15),e15133 (2019). [CrossRef] [PubMed] [Google Scholar]
- O. Moussa., H.Khachnaoui., R.Guetari., etal.Thyroid Nodules Classification and Diagnosis in Ultrasound Images using Fine-Tuning Deep Convolutional Neural Network, INT. J. IMAG.SYST. TECH. (2019). [Google Scholar]
- K. V. S. Sundar, K. T. Rajamani, S. S. S. Sai, Exploring Image Classification of Thyroid Ultrasound Images Using Deep Learning,ISMAC- CVB, 1635–1641(2018) [Google Scholar]
- M. Guo, Y. Du, Classification of Thyroid Ultrasound Standard Plane Images using ResNet-18 Networks,ASID, 324–328(2019) [Google Scholar]
- J. Wang, S. Li, W. Song, Learning from Weakly- Labeled Clinical Data for Automatic Thyroid Nodule Classification in Ultrasound Images, ICIP(2018.) [Google Scholar]
- O. Ronneberger, P. Fischer, T. Brox, U- Net:Convolutional Networks for Biomedical Image Segmentation,MICCAI,234–241(2015), [Google Scholar]
- D. P .Kingma, M.Welling. Auto-encoding variational bayes arXiv preprint arXiv:1312.6114(2013). [Google Scholar]
- M. Pesteie, P. Abolmaesumi, and R. N. Rohling, Adaptive augmentation of medical data using independently conditional variational auto- encoders,IEEE T. MED. IMAGING, 1–1(2019). [Google Scholar]
- K. Sohn, X.Yan, H. Lee, et al. Learning Structured Output Representation using Deep Conditional Generative Models,ICNIPS(2015) [Google Scholar]
- K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognition,CVPR,770–778(2016). [Google Scholar]
- N. Tajbakhsh JY Shin,S. R Gurudu et al., Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?,IEEE T. MED IMAGING,35,1299–1312(2016). [CrossRef] [Google Scholar]
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