Application of Hybrid Network of UNet and Feature Pyramid Network in Spine Segmentation

Spine segmentation plays an important role in spinal disease diagnosis and treatment, also, it is a fundamental procedure in some spine surgical navigation systems. In this paper, we proposed a hybrid network of Feature Pyramid Network (FPN) and UNet, and used it for vertebral body segmentation. Experiments were conducted with a T2-weighted lower spine MRI dataset. Experimental results show that our proposed network outperforms UNet and several other UNet based networks in spine segmentation. Quantitative analysis shows that segmentation accuracy of 99.5% can be achieved with this network.

Recommended citation: X. Liu, W. Deng and Y. Liu, "Application of Hybrid Network of UNet and Feature Pyramid Network in Spine Segmentation," 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Lausanne, Switzerland, 2021, pp. 1-6, doi: 10.1109/MeMeA52024.2021.9478765.
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