Multilevel space-time aggregation for bright field cell microscopy segmentation and tracking

Hans De Sterck, Tiffany Inglis, Geoffrey Sanders, Haig Djambazian, Robert Sladek, Saravanan Sundararajan, Thomas J Hudson

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)

Abstract

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called Segmentation by Weighted Aggregation technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant saliency measure is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments (object tunnels) that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.

Original languageEnglish
Article number582760
JournalInternational Journal of Biomedical Imaging
Volume2010
DOIs
Publication statusPublished - 2010
Externally publishedYes

Cite this