Three dimensional segmentation of fluorescence microscopy images using active surfaces

Kevin S. Lorenz, Paul Salama, Kenneth W. Dunn, Edward J. Delp

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

12 Scopus citations

Abstract

Three dimensional image volumes collected using optical microscopy exhibit many characteristics that cause difficulty in segmentation. These include decreasing image contrast with increasing tissue depth, poor edge detail with regard to cellular structures, and limited spatial resolution. This paper describes a three dimensional segmentation method utilizing active surfaces to segment microscopy image volumes. We demonstrate this method on a three dimensional sequence of images acquired from stationary/stabilized kidney tissue of a rat. Results from this method are compared against a prior pseudo-three dimensional segmentation method that analyzes slices on a single image-by-image basis, as well as against another native three dimensional segmentation method.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Pages1153-1157
Number of pages5
DOIs
StatePublished - Dec 1 2013
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: Sep 15 2013Sep 18 2013

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Other

Other2013 20th IEEE International Conference on Image Processing, ICIP 2013
CountryAustralia
CityMelbourne, VIC
Period9/15/139/18/13

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Keywords

  • biomedical optical imaging
  • image segmentation
  • optical microscopy

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Lorenz, K. S., Salama, P., Dunn, K. W., & Delp, E. J. (2013). Three dimensional segmentation of fluorescence microscopy images using active surfaces. In 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings (pp. 1153-1157). [6738238] (2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings). https://doi.org/10.1109/ICIP.2013.6738238