SeedWater Segmenter paper published
Research led by graduate student David Mashburn was recently published:
D.N. Mashburn, H.E. Lynch, X. Ma, M.S. Hutson (2012) “Enabling user-guided segmentation and tracking of surface-labeled cells in time-lapse image sets of living tissues” Cytometry A 81A(5): 409–418.
This article details a method for improving the interactivity of watershed segmentation algorithms. With this improvement, one can quickly segment tens to hundreds of cells in hundreds of time-lapse images. The python program that handles the segmentation and user interaction is known as SeedWater Segmenter (SWS), and is available for download under a BSD license at Google Code.