An Automated Method for Segmentation of Epithelial Cervical Cells in Images of ThinPrep

Authors:
Negar M. Harandi;Saeed Sadri;Noushin A. Moghaddam;Rassul Amirfattahi
Affiliations:
Digital Signal Processing Research Laboratory, Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran 84156-8311 and Medical Image and Signal Processing ...;Digital Signal Processing Research Laboratory, Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran 84156-8311 and Medical Image and Signal Processing ...;Medical Image and Signal Processing Research Center, Isfahan University of Medical Science, Isfahan, Iran 81746-73461;Digital Signal Processing Research Laboratory, Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran 84156-8311 and Medical Image and Signal Processing ...
Venue:
Journal of Medical Systems
Year:
2010

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Abstract

We present an automated method for segmentation of epithelial cells in images taken from ThinPrep scenes by a digital camera in a cytology lab. The method covers both steps of localization of cell objects in low resolution and detection of cytoplasm and nucleus boundary in high resolution. The underlying method makes use of geometric active contours as a powerful tool of segmentation. We also provide the analysis of the connected cells. For this purpose an automatic circular decomposition method is incorporated and adapted to the application by changing its segmentation condition. The results are evaluated numerically and compared with those of previous work in literature.