Segmentation of ascidian notochord cells in DIC timelapse images

Abstract

We have developed a method to automatically segment notochord cell boundaries from differential interference contrast (DIC) timelapse images of the elongating ascidian tail. The method is based on a specialized parametric active contour, the network snake, which can be initialized as a network of arbitrary but fixed topology and provides an effective framework for simultaneously segmenting multiple touching cells. Several modifications to the original network snake were necessary for high-quality segmentation, including linear Gaussian derivative filtering to reconstruct edge maps from DIC images and a new energy function to improve the segmentation of critical cell-cell vertices. We find that post-intercalation ascidian notochord cells exhibit two distinct cell behaviors: lateral cell edges expand along the AP axis while showing a rapid pulsatile behavior, whereas anterior and posterior cell edges contract smoothly.