29 January 2007 Classification of yeast cells from image features to evaluate pathogen conditions
Author Affiliations +
Abstract
Morphometrics from images, image analysis, may reveal differences between classes of objects present in the images. We have performed an image-features-based classification for the pathogenic yeast Cryptococcus neoformans. Building and analyzing image collections from the yeast under different environmental or genetic conditions may help to diagnose a new "unseen" situation. Diagnosis here means that retrieval of the relevant information from the image collection is at hand each time a new "sample" is presented. The basidiomycetous yeast Cryptococcus neoformans can cause infections such as meningitis or pneumonia. The presence of an extra-cellular capsule is known to be related to virulence. This paper reports on the approach towards developing classifiers for detecting potentially more or less virulent cells in a sample, i.e. an image, by using a range of features derived from the shape or density distribution. The classifier can henceforth be used for automating screening and annotating existing image collections. In addition we will present our methods for creating samples, collecting images, image preprocessing, identifying "yeast cells" and creating feature extraction from the images. We compare various expertise based and fully automated methods of feature selection and benchmark a range of classification algorithms and illustrate successful application to this particular domain.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter van der Putten, Laura Bertens, Jinshuo Liu, Ferry Hagen, Teun Boekhout, Fons J. Verbeek, "Classification of yeast cells from image features to evaluate pathogen conditions", Proc. SPIE 6506, Multimedia Content Access: Algorithms and Systems, 65060I (29 January 2007); doi: 10.1117/12.714072; https://doi.org/10.1117/12.714072
PROCEEDINGS
14 PAGES


SHARE
RELATED CONTENT


Back to Top