Abstract
Splitting touching cells is important for medical image processing and analysis system. In this paper, a novel strategy is proposed to separate ellipse-like or circle-like touching cells in which different algorithms are used according to the concave-point cases of touching domains. In the strategy, a concave-point extraction and contour segmentation methods for cells in series and in parallel are used for the images with distinct concave points, and an improved watershed algorithm with multi-scale gradient and distance transformation is adopted for the images with un-distinct or complex concave points. In order to visualize each whole cell, ellipse fitting is used to process the segments. Experimental results show that, for the cell images with distinct concave points, both of the two algorithms can achieve good separating results, but the concave-point based algorithm is more efficient. However, for the cell images with unobvious or complex concave points, the improved watershed based algorithm can give satisfying segmenting results.
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Hong Song received her PhD degree in computer science and technology from Beijing Institute of Technology in 2003. She is currently an associate professor in the School of Software, Beijing Institute of Technology, China. Her current research interests include image processing, machine vision, and computer graphics.
Qingjie Zhao received her PhD degree in computer science and technology from Tsinghua University in 2003. She is currently a professor in the School of Computer Science and Technology, Beijing Institute of Technology, China. Her current research interests include image processing, machine vision, and computing intelligence.
Yinghong Liu received her MS degree from School of Computer Science and Technology, Beijing Institute of Technology in 2012. She now works in Lenovo, China.
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Song, H., Zhao, Q. & Liu, Y. Splitting touching cells based on concave-point and improved watershed algorithms. Front. Comput. Sci. 8, 156–162 (2014). https://doi.org/10.1007/s11704-013-3130-2
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DOI: https://doi.org/10.1007/s11704-013-3130-2