The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results

October 19, 2020 · Entered Twilight · 🏛 arXiv.org

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Repo contents: README.md, eval.py, test.json, train.json

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 arXiv ID 2010.10298 Category eess.IV: Image & Video Processing Cross-listed cs.CV Citations 0 Venue arXiv.org Repository https://github.com/Deepwise-AILab/ChestX-Det10-Dataset ⭐ 34 Last Checked 2 months ago

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.