Segmentation of kidney tumor by multi-resolution VB-nets
Guangrui Mu, Zhiyong Lin, Miaofei Han, Guang Yao, Yaozong Gao · 2019
Accurate segmentation of kidney tumors can assist doctors to diagnose diseases, and to improve treatment planning, which is highly demanded in the clinical practice.In this work, we propose multi-resolution 3D V-Net networks to automatically segment kidney and renal tumor in computed tomography (CT) images.Specifically, we adopt two resolutions and propose a customized V-Net model called VB-Net for both resolutions.The VB-Net model in the coarse resolution can robustly localize the organs, while the VB-Net model in the fine resolution can accurately refine the boundary of each organ or lesion.We experiment in the KiTS19 challenge, which shows promising performance.