SegTHOR2019
SegTHOR Challenge: Segmentation of THoracic Organs at Risk in CT Images

Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images (SegTHOR2019)

co-located with the 16th International Symposium on Biomedical Imaging (ISBI)

Caroline Petitjean*
Su Ruan*
Zoé Lambert**
Bernard Dubray*,***

Table of Contents

• Segmentation of CT Thoracic Organs by Multi-resolution VB-nets
  Miaofei Han, Guang Yao, Wenhai Zhang, Guangrui Mu, Yiqiang Zhan, Xiang Zhou, Yaozong Gao
• Multi-task Learning for the Segmentation of Thoracic Organs at Risk in CT images
  Tao He, Jixiang Guo, Jianyong Wang, Xiuyuan Xu, Zhang Yi
• A Cascaded Two-step Approach For Segmentation of Thoracic Organs
  Sekeun Kim, Yeonggul Jang, Kyunghoon Han, Hackjoon Shim, Hyuk-Jae Chang
• Two-stage Network for OAR segmentation
  Pan Chen, Chenghai Xu, Xiaoying Li, Yingying Ma, Fenglong Sun
• Segmentation of Thoracic Organs at Risk in CT Images Combining Coarse and Fine Network
  Li Zhang, Lishen Wang, Yijie Huang, Huai Chen
• Dilated U-Net based Segmentation of Organs at Risk in Thoracic CT Images
  Manoj Satya Kumar Gali, Neerja Garg, Srikanth Vasamsetti
• 3D Enhanced Multi-scale Network for Thoracic Organs Segmentation
  Qin Wang, Weibing Zhao, Chunhui Zhang, Liyue Zhang, Changmiao Wang, Zhen Li, Shuguang Cui, Guanbin Li
• Segthor: Segmentation of Thoracic Organs at Risk in CT Images
  Vladimir Kondratenko, Dmitry Denisenko, Artem Pimkin, Mikhail Belyaev
• Segmentation of Thoracic Organs Using Pixel Shuffle
  Dmitry Lachinov
• Multi-organ Segmentation using Simplified Dense V-net with Post-processing
  Ming Feng, Weiquan Huang, Yin Wang, Yuxia Xie
• Automatic Segmentation of Organs at Risk in Thoracic CT scans by Combining 2D and 3D Convolutional Neural Networks
  Louis van Harten, Julia Noothout, Joost Verhoeff, Jelmer Wolterink, Ivana Išgum
• A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT
  Sulaiman Vesal, Nishant Ravikumar, Andreas Maier