An evaluation of U-Net in Renal Structure Segmentation
This work addresses renal cancer treatment applications by applying existing methods to a new medical imaging dataset, but it is incremental as it only evaluates standard U-Net variants.
The researchers evaluated several U-Net variants for segmenting renal structures from CT angiography data in the KiPA 2022 challenge, selecting the best models for submission without reporting specific performance metrics.
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.