Segmentation of ascidian notochord cells in DIC timelapse images
Boguslaw Obara1, Michael Veeman, Jae Hyeok Choi
1Center for BioImage Informatics, Department of Electrical Computer Engineering, University of California, Santa Barbara, California, USA. boguslaw.obara@oerc.ox.ac.uk
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.


