Abstract
Kidney cancer is one of the most common malignant tumors in the world. Automatic segmentation of kidney, kidney tumor, and kidney cyst is a essential tool for kidney cancer surgery. In this paper, we use a coarse-to-fine framework which is based on the nnU-Net and achieve accurate and fast segmentation of the kidney and kidney mass. The average Dice and surface Dice of segmentation predicted by our method on the test are 0.9077 and 0.8262, respectively. Our method outperformed all other teams and achieved \(1^{st}\) in the KITS2021 challenge.
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References
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Acknowledgment
We would like to express our gratitude to the KiTS2021 organizers and the nnU-Net team. We also want to say thanks to Nicholas Heller and Fabian Isensee for their kind help.
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Zhao, Z., Chen, H., Wang, L. (2022). A Coarse-to-Fine Framework for the 2021 Kidney and Kidney Tumor Segmentation Challenge. In: Heller, N., Isensee, F., Trofimova, D., Tejpaul, R., Papanikolopoulos, N., Weight, C. (eds) Kidney and Kidney Tumor Segmentation. KiTS 2021. Lecture Notes in Computer Science, vol 13168. Springer, Cham. https://doi.org/10.1007/978-3-030-98385-7_8
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DOI: https://doi.org/10.1007/978-3-030-98385-7_8
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