Position-Prior Clustering-Based Self-attention Module for Knee Cartilage Segmentation
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-16443-9_19
Reference12 articles.
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2. Marinetti, A., et al.: Morphological MRI of knee cartilage: repeatability and reproducibility of damage evaluation and correlation with gross pathology examination. Eur. Radiol. 30(6), 3226–3235 (2019). https://doi.org/10.1007/s00330-019-06627-5
3. Gatti, A.A., Maly, M.R.: Automatic knee cartilage and bone segmentation using multi-stage convolutional neural networks: data from the osteoarthritis initiative. Magn. Reson. Mater. Phys., Biol. Med. 34(6), 859–875 (2021). https://doi.org/10.1007/s10334-021-00934-z
4. Ambellan, F., Tack., Ehlke, M., Zachow, S.: Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: data from the osteoarthritis initiative. Med. Image Anal. 52, 109–118 (2019)
5. Lecture Notes in Computer Science;C Tan,2019
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