Abstract
Ciliary beating frequency (CBF) estimation is of high interest for the diagnosis and therapeutic assessment of defective mucociliary clearance diseases. Image-based methods have recently become the focus of accurate CBF measurement. The influence from the moving ciliated cell however makes the processing a challenging problem. In this work, we present a registration method for cell movement alignment, based on cell contour segmentation. We also propose a filter feature-based ciliary motion representation, which can better characterize the periodical changes of beating cilia. Experimental results on microscopic time sequence human primary ciliated cell images show the accuracy of our method for CBF computation.
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Zhang, F. et al. (2015). Motion Representation of Ciliated Cell Images with Contour-Alignment for Automated CBF Estimation. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9351. Springer, Cham. https://doi.org/10.1007/978-3-319-24574-4_36
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DOI: https://doi.org/10.1007/978-3-319-24574-4_36
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