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{\large Hans De Sterck \\
{\bf Multilevel Space-Time Aggregation for Cell Microscopy Segmentation and Tracking}}

University of Waterloo \\ 200 University Avenue West \\ Waterloo \\ Ontario N2L 3G1 \\ Canada
\\
{\tt hdesterck@uwaterloo.ca}\\
Tiffany Inglis\\
Geoffrey Sanders\\
Haig Djambazian\\
Robert Sladek\\
Saravanan Sundararajan\\
Thomas Hudson\end{center}

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, 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, as expected, the addition of multilevel intensity variance (as a
measure of texture) to the feature vector of each aggregate leads to
improved 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.

Application of the algorithm to segmentation and road finding for
satellite images is also briefly discussed.


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