Registration of in vivo fluorescence endomicroscopy images based on feature detection

Feng Zhao, Lee Sing Cheong, Feng Lin, Kemao Qian, Hock Soon Seah, Sun Yuan Kung

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

4 Scopus citations

Abstract

The confocal fluorescence endomicroscopy is an emerging technology for imaging the living subjects inside the animals and human bodies. However, the acquired images vary, due to two degrees of freedom-tissue movement and tissue expansion/contraction. This makes the 3D reconstruction of them difficult and thus limits the clinic applications. In this chapter, we propose a feature-based registration algorithm to correct the distortions between these fluorescence images. The good alignment enables us to reconstruct and visualize the 3D structure of the living cells and tissues in real time, which provides the opportunity for the clinicians to diagnose various diseases, including the early-stage cancers. Experimental results on a collection of more than 300 confocal fluorescence images of the gerbil brain microvasculature clearly demonstrate the effectiveness and accuracy of our method.

Original languageEnglish (US)
Title of host publicationAdvances in Computational Biology
EditorsHamid Arabnia
Pages535-548
Number of pages14
DOIs
StatePublished - 2010

Publication series

NameAdvances in Experimental Medicine and Biology
Volume680
ISSN (Print)0065-2598

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)

Keywords

  • Biomedical image processing
  • Computational system
  • Confocal fluorescence image
  • Endomicroscopic imaging
  • Image alignment

Fingerprint Dive into the research topics of 'Registration of in vivo fluorescence endomicroscopy images based on feature detection'. Together they form a unique fingerprint.

Cite this