An evaluation of U-Net in Renal Structure Segmentation

• URL: http://arxiv.org/abs/2209.02247v1
• Date: Tue, 6 Sep 2022 06:53:41 GMT
• Title: An evaluation of U-Net in Renal Structure Segmentation
• Authors: Haoyu Wang, Ziyan Huang, Jin Ye, Can Tu, Yuncheng Yang, Shiyi Du, Zhongying Deng, Chenglong Ma, Jingqi Niu, Junjun He
• Abstract summary: Kidney PArsing(KiPA 2022) Challenge aims to build a fine-grained multi-structure dataset. We evaluated several U-Net variants and selected the best models for the final submission.
• Score: 13.7055816814391
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Renal structure segmentation from computed tomography angiography~(CTA) is essential for many computer-assisted renal cancer treatment applications. Kidney PArsing~(KiPA 2022) Challenge aims to build a fine-grained multi-structure dataset and improve the segmentation of multiple renal structures. Recently, U-Net has dominated the medical image segmentation. In the KiPA challenge, we evaluated several U-Net variants and selected the best models for the final submission.

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