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.
翻译:计算机辅助肾癌治疗应用中,许多计算机辅助肾癌治疗应用都需要从计算成的断层血管成像到(CTA)的再红结构分割。 肾上腺 Parsing~ (KIPA 2022) 挑战的目的是建立一个精细的多结构数据集,改善多肾结构的分离。 最近, U-Net在医学图像分割中占据了主导地位。 在KIPA的挑战中,我们评估了几个U-Net变量,并选择了最终提交的最佳模型。