Segmentation of CT Kidney and kidney tumor by MDD-Net

Authors
Chen, Ball

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

Abstract
Accurate segmentation of kidney and kidney tumor is an important step for treatment. Due to the wide variety in kidney and kidney tumor morphology, it’s really a challenging task. In this work, we propose the Multi-level double-dimension Network to automatically segmentat kidney and kidney tumor. We select the modified FPN as backbone and aggregate different scale information from multi levels to make the final prediction. In the KiTS 2019, we use 170 CT scans for training and the remaining 40 CT scans are used to evaluate the model. At the time of submission, we obtained the best result by averaging multiple models.

Identifiers
doi: 10.24926/548719.010