Automated quantification of the phagocytosis of Aspergillus fumigatus conidia by a novel image analysis algorithm.

ABSTRACT: Studying the pathobiology of the fungus Aspergillus fumigatus has gained a lot of attention in recent years. This is due to the fact that this fungus is a human pathogen that can cause severe diseases, like invasive pulmonary aspergillosis in immunocompromised patients. Because alveolar macrophages belong to the first line of defense against the fungus, here, we conduct an image-based study on the host-pathogen interaction between murine alveolar macrophages and A. fumigatus. This is achieved by an automated image analysis approach that uses a combination of thresholding, watershed segmentation and feature-based object classification. In contrast to previous approaches, our algorithm allows for the segmentation of individual macrophages in the images and this enables us to compute the dist

SUBMITTER: Kraibooj K 

PROVIDER: S-EPMC4460560 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature