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Method of real-time tracking for respiratory motion based on SIFT feature matching

  • Dong Feng
  • , Li Ning Sun
  • , Chang Hai Ru*
  • *Corresponding author for this work
  • Soochow University

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a new non-contact method of cancer detection based on SIFT feature matching is proposed to track real-time the respiratory motion. And a new camera calibration method based on planar and 3D checkerboard templates is proposed to get high accuracy calibration parameters. Experiment results show that cameras calibration accuracy is 0.0365 mm and the biggest movement scope of the marker is not lager than 1.5 mm between the vision measurement and practical measurement in a breathing cycle and can achieve the real-time tracking for respiratory motion.

Original languageEnglish
Pages (from-to)3897-3902
Number of pages6
JournalInformation Technology Journal
Volume12
Issue number16
DOIs
StatePublished - 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Binocular vision
  • Camera calibration
  • Precise radiotherapy
  • Real-time tracking
  • Respiratory motion
  • SIFT feature matching

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