Coarse to Fine Framework for Kidney Tumor Segmentation

Authors
Liu, Shuolin

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

Abstract
Accurate segmentation of kidney tumor is a key step in image-guided radiation therapy. However, shapes, scales and appearance vary greatly from patient to patient, which pose a serious challenge to segment targets correctly. In this work, we proposed a coarse-to-fine framework to automatically segment kidney and tumor computed tomography (CT) images. Specifically, we adopt two resolutions and propose a improved 3D U-Net network for kidney tumor segmentation. The model in the coarse resolution can robustly localize the kidney, while the model in the fine resolution can accurately refine the boundary of kidney and tumor.

Identifiers
doi: 10.24926/548719.006