English

The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results

Image and Video Processing 2020-10-23 v2 Computer Vision and Pattern Recognition
Authors: Jie Lian , Jingyu Liu , Yizhou Yu , Mengyuan Ding , Yaoci Lu , Yi Lu , Jie Cai , Deshou Lin , Miao Zhang , Zhe Wang , Kai He , Yijie Yu
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Abstract

The detection of thoracic abnormalities challenge is organized by the Deepwise AI Lab. The challenge is divided into two rounds. In this paper, we present the results of 6 teams which reach the second round. The challenge adopts the ChestX-Det10 dateset proposed by the Deepwise AI Lab. ChestX-Det10 is the first chest X-Ray dataset with instance-level annotations, including 10 categories of disease/abnormality of 3,543 images. The annotations are located at https://github.com/Deepwise-AILab/ChestX-Det10-Dataset. In the challenge, we randomly split all data into 3001 images for training and 542 images for testing.

Keywords

thoracic abnormality detection ChestX-Det10 chest X-ray instance-level annotation challenge results dataset

Cite

@article{arxiv.2010.10298,
  title  = {The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results},
  author = {Jie Lian and Jingyu Liu and Yizhou Yu and Mengyuan Ding and Yaoci Lu and Yi Lu and Jie Cai and Deshou Lin and Miao Zhang and Zhe Wang and Kai He and Yijie Yu},
  journal= {arXiv preprint arXiv:2010.10298},
  year   = {2020}
}

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