Abstract
Muco-ciliary clearance is the airway first mechanism of defence against environmental attacks such as microorganisms or pollution. Cilia motility impairment can be either of genetic (primary ciliary dyskinesia) or acquired origin (environmental attacks), entailing chronic diseases. It is of interest for practitioners to evaluate cilia beating frequency easily, robustly and reliably. As yet, no fully automatized method is available. 2 Methods Ciliated cells were sampled in patients by brushing nasal mucosa and cilia beating was recorded using high speed video microscopy. We first estimated and removed the sensor pattern. We then stabilized the sequence assuming rigid transforms. We retained only the moving parts of the sequence and, after deblurring, characterized and segmented the moving parts in several regions of interest. The frequency was estimated for each region.
Highlights
Cilia motility impairment can be either of genetic or acquired origin, entailing chronic diseases
An estimation of frequencies for each beating part is the final result. With this new method, we propose a fully automatic estimation of cilia beating frequencies, which is able to deal with acquisition artifacts, such as sensor patterns, vibrations and noise, and with the variety of frequencies we Submit your manuscript to BioMed Central and take full advantage of:
ConclusionWe propose a fully automatic estimation of cilia beating frequencies, which is able to deal with acquisition artifacts, such as sensor patterns, vibrations and noise, and with the variety of frequencies we Submit your manuscript to BioMed Central and take full advantage of:
Summary
Muco-ciliary clearance is the airway first mechanism of defence against environmental attacks such as microorganisms or pollution. Cilia motility impairment can be either of genetic (primary ciliary dyskinesia) or acquired origin (environmental attacks), entailing chronic diseases. It is of interest for practitioners to evaluate cilia beating frequency robustly and reliably. We believe this may be a useful method for practitioners. Authors’ details 1Laboratoire d’Informatique Gaspard Monge, CNRS UMR8049, Université Paris-Est ESIEE, Marne-La-Vallée, France. Authors’ details 1Laboratoire d’Informatique Gaspard Monge, CNRS UMR8049, Université Paris-Est ESIEE, Marne-La-Vallée, France. 2Inserm U955, Eq13, Créteil 94000, Créteil, France. 3Université Paris-Est, Faculté de Médecine, Créteil 94000, Créteil, France. 4CNRS ERL 7240, Créteil 94000, Créteil, France
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
