Ensemble U-Net for 2019 Kidney Tumor Segmentation Challenge

Authors
Wu, Ting

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

Abstract
Its known to us all that convolutional network makes medical processing more accurate and efficient as a significant tool for assisting doctors. In deed,aiming at kidney and diversity of kidney tumor,there already have various effective segmentation results from networks learning, and they are more comparable. Therefore,methods based on networks has become a mainstream in image processing.For this MICCAI kidney and kidney tumor segmentation challenges, we proposed our own scheme.We are inspired by U-Net,experiment in five U-Net on 300 abdominal CT scan of arterial phase in patients with renal cell carcinoma, then take all results as an ensemble and use it as the final result.

Identifiers
doi: 10.24926/548719.011