## 3 Results and Discussion
### Automated and High-Throughput Counting of Chrysotile Using DM-HTM
Representative reflection and fluorescence images of the mixed chrysotile and amosite are given in Figure 5. The contrast of the reflection images taken at normal illumination level is much higher than those used for Figure 6(b) and the background noise such as debris and air bubble is noticeable in some images (Figure 7(c)). Figure 7(a) shows the automatic counts of the mixed asbestos samples against chrysotile concentrations. Since the amosite concentration is inversely related with the chrysotile concentration and the size of amosite is much smaller than chrysotile in the mixed sample, the amount of amosite is greater than chrysotile. Therefore the total fiber count from the reflection image analysis is decreased with increasing chrysotile concentration. However, since only the chrysotile fibers are visible in the fluorescence mode, the number of fibers determined by fluorescence image analysis is directly proportional to the chrysotile concentration. Figure 7(b) shows the automatic counts of chrysotile samples against chrysotile concentrations. Reflection image analysis resulted in fluctuation and overestimation of the fiber counts in the sample slide where air bubbles were formed, by erroneously recognizing their menisci as fibers. In contrast, the fiber count from fluorescence image analysis is linearly increased with the chrysotile concentration regardless of background noise level in the sample slide. Non-fluorescent debris and bubble images appeared in the reflection image are removed completely in the fluorescence image as exhibited in Figure 7(c,d). This tendency to \"over count\" has not been considered in the existing PCM method that  
Figure 7: Results from analyses of reflection and fluorescence images. (**a**) Automatic fiber counts of the mixed asbestos samples (chrysotile and amosite) against chrysotile concentrations. (**b**) Automatic fiber counts of chrysotile samples against chrysotile concentrations. Representative reflection image (**c**) with high background noise level and corresponding fluorescence image (pseudo-colored red) (**d**). \(\text{Bar}=100\) μm. is based on manual counting in bright-field mode by human naked eye. We may reveal and compensate those biased errors accompanied by manual counting through our DM-HTM method. We enhanced the sensitivity and selectivity of the HTM method to detect chrysotile exclusively from low-concentration samples containing small and thin fibers and asbestos of different types by the fluorescently-labeled chrysotile-adhesive protein and the DM-HTM system. In particular the background noise, which is often considered to be fibers in bright-field imaging mode, was reduced by approximately 90% in the fluorescence imaging mode. It was reported that chrysotile fibers that are as thin as 30-35 nm can be detected using Cy3-labeled DksA protein [16]. It is promising that the proposed DM-HTM method should realize fully automated counting of airborne asbestos if combined with more advanced software that can identify overlapping and branching fibers and distinguish between fibers and oval-shaped debris.