Tumor size measurement and feature point extraction using an endoscope

Jong Wook Lim, Dong Gi Woo, Hoon Jai Chun, Bora Keum, Jong Jin Hyun, Young Joong Kim, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recently, a development of the medical instrument using the vision information is brisk. Especially, extracting the 3-dimension information from 2-dimension image is the one of the major research topics. This paper proposes the method to measure tumor size by the 3-dimension information extraction, the triangulation using the extracted 3-dimension information and the camera geometry. To extract the 3-dimension information, the Hough circle transform and triangulation are used. The Hough circle transform is used to extract a feature point from tumor models for the 3-dimension information recovery. An extracted feature point is used for recovering the depth information from the 2-dimension tumor stereo images. A tumor size measurement is done by triangulation using the depth information and camera internal parameters. Matlab and Visual C++ are used for simulation.

Original languageEnglish
Title of host publicationICCAS 2010 - International Conference on Control, Automation and Systems
Pages105-108
Number of pages4
Publication statusPublished - 2010
EventInternational Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of
Duration: 2010 Oct 272010 Oct 30

Publication series

NameICCAS 2010 - International Conference on Control, Automation and Systems

Other

OtherInternational Conference on Control, Automation and Systems, ICCAS 2010
Country/TerritoryKorea, Republic of
CityGyeonggi-do
Period10/10/2710/10/30

Keywords

  • 3-D reconstruction
  • Endoscope
  • Stereo vision

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Tumor size measurement and feature point extraction using an endoscope'. Together they form a unique fingerprint.

Cite this