Automated Detection of Lung Nodules in CT Images with 3D Convolutional Neural Networks

Cheng Dai, Bo Xiao*, Yun Chen, Yujiao Du, Yu Liang, Kai Zhao, Liping Yan

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

Accurate lung nodule detection in computed tomography (CT) images is a critical step in diagnosing lung cancer. This paper proposes an efficient model to build a Computer-Aided Detection (CADe) system for lung nodule detection, which points out a way to enhance a patient's chance of survival. We first introduce a specially designed three-dimension convolutional neural networks (3D CNN) for candidate detection that takes into account of nodules with various sizes. Then, another 3D CNN is presented for the subsequent false positive reduction. Experimental results of the Tianchi Medical AI Challenge demonstrate the superior detection performance of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages55-59
Number of pages5
ISBN (Electronic)9781538660669
DOIs
Publication statusPublished - 6 Nov 2018
Event6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 - Guiyang, China
Duration: 22 Aug 201824 Aug 2018

Publication series

NameProceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018

Conference

Conference6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018
Country/TerritoryChina
CityGuiyang
Period22/08/1824/08/18

Keywords

  • 3D CNN
  • CAD
  • lung nodule detection

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