Cheng, J., Xiong, W., Gu, Y., Chia, S.-C., Wang, Y., & Lim, J.-H. (2015). A Three-Color Coupled Level-Set Algorithm for Simultaneous Multiple Cell Segmentation and Tracking. In Computer Vision -- ACCV 2014 (pp. 268–283). Springer International Publishing. https://doi.org/10.1007/978-3-319-16811-1_18
Abstract:
High content computational analysis of time-lapse microscopic cell images requires accurate and efficient segmentation and tracking. In this work, we introduce “3LS”, an algorithm using only three level sets to segment and track arbitrary number of cells in time-lapse microscopic images. The cell number and positions are determined in the first frame by extracting concave points and fitting ellipses after initial segmentation. We construct a graph representing cells and the background with vertices and their adjacency relationships with edges. Each vertex of the graph is assigned with a color tag by applying a vertex coloring algorithm. In this way, the boundary of each cell can be embedded in one of three level set functions. The “3LS” algorithm is implemented in an existing coupled active contour framework (nLS) [1] to handle overlapped cells during segmentation. However, we improve nLS using a new volume conservation constraint (VCC) to prevent shrinkage or expansion on whole cell boundaries and produce more accurate segmentation and tracking of touching cells. When tested on four different time-lapse image sequences, the 3LS outperforms the original nLS and other relevant state-of-the-art counterparts in both segmentation and tracking however with a notable reduction in computational time.
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Publisher Copyright
Funding Info:
There was no specific funding for the research done
Description:
This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-16811-1_18