Airborne asbestos fibers detection in microscope images using re-initialization free active contours

Abstract

Breathing in asbestos fibers can lead to a number of diseases, the fibers become trapped in the lung and cannot be removed by either coughing or the person's immune system. Atmospheric concentrations of carcinogenic asbestos fibers, have traditionally been measured visually using phase contrast microscopy. However, because this measurement method requires great skill, and has poor reproducibility and objectivity, the development of automatic counting methods has been long anticipated. In this paper we proposed an automated fibers detection method based on a variational formulation of geometric active contours that forces the level set function to be close to signed distance function and therefore completely eliminates the need of the costly re-initialization procedure. The method was evaluated using a ground truth of 29 manually annotated images. The results were encouraging for the further development of the proposed method.