activity
20162019
most citedThe Importance of Skip Connections in Biomedical Image Segmentation

112 citations · 117 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2019

The Liver Tumor Segmentation Benchmark (LiTS)

Patrick Bilic, Patrick Christ, Hongwei Bran Li +106

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…

cs.LG2018

On the Importance of Attention in Meta-Learning for Few-Shot Text Classification

Xiang Jiang, Mohammad Havaei, Gabriel Chartrand +5

Current deep learning based text classification methods are limited by their ability to achieve fast learning and generalization when the data is scarce. We address this problem by…

cs.CV2017

Liver lesion segmentation informed by joint liver segmentation

Eugene Vorontsov, An Tang, Chris Pal +1

We propose a model for the joint segmentation of the liver and liver lesions in computed tomography (CT) volumes. We build the model from two fully convolutional networks, connecte…

cs.CV2017★ 5 cited

Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation

Michal Drozdzal, Gabriel Chartrand, Eugene Vorontsov +6

In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Netwo…

cs.CV2016★ 112 cited

The Importance of Skip Connections in Biomedical Image Segmentation

Michal Drozdzal, Eugene Vorontsov, Gabriel Chartrand +2

In this paper, we study the influence of both long and short skip connections on Fully Convolutional Networks (FCN) for biomedical image segmentation. In standard FCNs, only long s…