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The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results

Authors :
Lian, Jie
Liu, Jingyu
Yu, Yizhou
Ding, Mengyuan
Lu, Yaoci
Lu, Yi
Cai, Jie
Lin, Deshou
Zhang, Miao
Wang, Zhe
He, Kai
Yu, Yijie
Lian, Jie
Liu, Jingyu
Yu, Yizhou
Ding, Mengyuan
Lu, Yaoci
Lu, Yi
Cai, Jie
Lin, Deshou
Zhang, Miao
Wang, Zhe
He, Kai
Yu, Yijie
Publication Year :
2020

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.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1228440477
Document Type :
Electronic Resource