A Coarse Feature Reuse Deep Neural Network for CXR Lesion Detection

Xinquan Yang, Xuechen Li, Linlin Shen, Min Cao, Changen Zhou

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Lung disease screening using Chest x-ray (CXR) radiographs can obviously decrease the incidence of lung cancer. Using computer-aided diagnosis system to assist doctors in lung disease screening can greatly improve the diagnosis efficiency. In this paper, a coarse feature reuse deep neural network for CXR lesion detection is proposed. Firstly, we design a coarse feature reuse (CFR) block that can reuse low-level semantic features and extract high-level semantic information, which is used to replace the max-pooling layer in the shallow part of the network to achieve better feature extraction. A novel backbone network - RRCNet, which combines RepVGG block and Resblock, is proposed. The RepVggblock is used for better feature extraction at shallow layers and the Resblock is used for better feature fusion at deep layers. Extensive experiments on VinDr-CXR dataset demonstrate that our RRCNet-based detection network outperformes other classic detectors on both mAP (17.67%) and inference speed (0.1426s).

Original languageEnglish
Title of host publicationProceedings - 11th International Conference on Information Technology in Medicine and Education, ITME 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages307-313
Number of pages7
ISBN (Electronic)9781665406796
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event11th International Conference on Information Technology in Medicine and Education, ITME 2021 - Wuyishan, China
Duration: 19 Nov 202121 Nov 2021

Publication series

NameProceedings - 11th International Conference on Information Technology in Medicine and Education, ITME 2021

Conference

Conference11th International Conference on Information Technology in Medicine and Education, ITME 2021
Country/TerritoryChina
CityWuyishan
Period19/11/2121/11/21

Keywords

  • chest x-ray radiograph
  • computer-aided detection
  • medical image
  • neural network
  • pulmonary lesion detection

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Health Informatics
  • Education
  • Management Information Systems
  • Computer Networks and Communications

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