Segmentation of Lymph Nodes in Ultrasound Images Using U-Net Convolutional Neural Networks and Gabor-Based Anisotropic Diffusion-Reference-Cited by-同舟云学术

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Segmentation of Lymph Nodes in Ultrasound Images Using U-Net Convolutional Neural Networks and Gabor-Based Anisotropic Diffusion

Published:2021-11-26 Issue:6 Volume:41 Page:942-952
ISSN:1609-0985
Container-title:Journal of Medical and Biological Engineering
language:en
Short-container-title:J. Med. Biol. Eng.

Author:

Chen Haobo,Wang Yuqun,Shi Jie,Xiong Jingyu,Jiang Jianwei,Chang Wanying,Chen Man,Zhang Qi

Funder

national natural science foundation of china

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s40846-021-00670-8.pdf

Reference38 articles.

1. Evans, K. D., Sammet, S., Ramos, Y., & Knopp, M. V. (2008). Image segmentation for evaluating axillary lymph nodes. Journal of Diagnostic Medical Sonography, 24(6), 329–336.

2. Zhang, Y., Ying, M. T., Yang, L., Ahuja, A. T., & Chen, D. Z. (2016, December). Coarse-to-fine stacked fully convolutional nets for lymph node segmentation in ultrasound images. In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 443-448). IEEE.

3. Pham, D. L., Xu, C., & Prince, J. L. (2000). A survey of current methods in medical image segmentation. Annual Review of Biomedical Engineering, 2, 315–337.

4. Sarle, W. S. (2012). Algorithms for Clustering Data. Technometrics, 32(2), 227–229.

5. Zhang, K., Zhang, L., Song, H., et al. (2013). Reinitialization-free level set evolution via reaction diffusion. IEEE Transactions on Image Processing, 22(1), 258–271.

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