Classification Model for Easily Confused Breast Ultrasound Image Based on Shape and Texture Features
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0923-0_6
Reference15 articles.
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2. Egoshin, I.A., Pasynkov, D.V., Kolchev, A.A., Kliouchkin, I.V., Pasynkova, O.O.: Segmentation of breast focal lesions on the ultrasound image. Biomed. Eng. 54(2), 99–103 (2020). https://doi.org/10.1007/s10527-020-09982-6
3. Cho, B.H., et al.: Ultrasound breast lesion segmentation using adaptive parameters. In: Presented at the SPIE Medical Imaging, San Diego, California, USA March 18 (2014). https://doi.org/10.1117/12.2041893
4. Xue, C., et al.: Global guidance network for breast lesion segmentation in ultrasound images. Med. Image Anal. 70, 101989 (2021). https://doi.org/10.1016/j.media.2021.101989
5. Zhuang, Z., Li, N., Raj, A.N.J., Mahesh, V.G.V., Qiu, S.: An RDAU-NET model for lesion segmentation in breast ultrasound images. PLoS ONE 14(8), e0221535 (2019). https://doi.org/10.1371/journal.pone.0221535
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