A Recursive and Model-Constrained Region Splitting Algorithm for Cell Clump Decomposition

Abstract

Decomposition of cells in clumps is a difficult segmentation task requiring region splitting techniques. Techniques that do not employ prior shape constraints usually fail to achieve accurate segmentation. Those using shape constraints are unable to cope with large clumps and occlusions. In this work, we propose a model-constrained region splitting algorithm for cell clump decomposition. We build the cell model using joint probability distribution of invariant shape features. The shape model, the contour smoothness and the gradient information along the cut are used to optimize the splitting in a recursive manner. The short cut rule is also adopted as a strategy to speed up the process. The algorithm performs well in validation experiments using 60 images with 4516 cells and 520 clumps.