A novel approach for the automatic estimation of the ciliated cell beating frequency

The qualitative and quantitative evaluation of nasal epithelial cells is interesting in chronic infectious and inflammatory pathologies of the nose and sinuses. Among the cells of the population of the nasal mucosa, ciliated cells are particularly important. In fact, the observation of these cells is essential to investigate primary ciliary dyskinesia, a rare and severe disease associated with other serious diseases such as respiratory diseases, situs inversus, heart disease, and male infertility. Biopsy or brushing of the ciliary mucosa and assessment of ciliary function through measurements of the Ciliary Beating Frequency (CBF) are usually required to facilitate diagnosis. Therefore, low-cost and easy‐to‐use technologies devoted to measuring the ciliary beating frequency are desirable. We have considered related works in this field and noticed that up to date an actually usable system is not available to measure and monitor CBF. Moreover, performing this operation manually is practically unfeasible or demanding. For this reason, we designed BeatCilia, a low cost and easy‐to-use system, based on image processing techniques, with the aim of automatically measuring CBF. This system performs cell Region of Interest (RoI) detection basing on dense optical flow computation of cell body masking, focusing on the cilia movement and taking advantage of the structural characteristics of the ciliated cell and CBF estimation by applying a fast Fourier transform to extract the frequency with the peak amplitude. The experimental results show that it offers a reliable and fast CBF estimation method and can efficiently run on a consumer grade smartphone. It can support rhinocytologists during cell observation, significantly reducing their efforts.