KiTS challenge: VNet with attention gates and deep supervision

Authors
Tureckova, Alzbeta
Turecek, Tomas
Kominkova, Zuzana
Rodŕıguez-Sánchez, Antonio

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

Abstract
This paper presents the 3D fully convolutional neural network extended by attention gates and deep supervision layers. The model is able to automatically segment the kidney and kidney-tumor from arterial phase abdominal computed tomography (CT) scans. It was trained on the dataset proposed by the Kidney Tumor Segmentation Challange 2019. The best solution reaches the dice score 96, 43± 1, 06 and 79, 94± 5, 33 for kidney and kidney-tumor labels, respectively. The implementation of the proposed methodology using PyTorch is publicly available at github.com/tureckova/Abdomen-CT-Image-Segmentation.

Identifiers
doi: 10.24926/548719.014