KiTS challenge: VNet with attention gates and deep supervision

Alzbeta Tureckova, Tomas Turecek, Zuzana Kominkova, Antonio Rodŕıguez-Sánchez
2019 Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19   unpublished
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
more » ... methodology using PyTorch is publicly available at github.com/tureckova/Abdomen-CT-Image-Segmentation.
doi:10.24926/548719.014 fatcat:cwpnkjz6qzcd3gwkfrtm4qm5gu