The evaluation of new therapies to treat allergic asthma makes frequent use of histological studies. Some of them are based on microscope observation of stained paraffin lung sections to quantify cellular infiltrate, an effect directly related to allergic processes. Currently, there is no software tool available for doing this quantification automatically. This paper presents a methodology and a software tool for the quantification of cellular infiltrate in lung tissue images in an allergic asthma mouse model. The image is divided into regions of equal size, which are then classified by means of a segmentation algorithm based on texture analysis. The classification uses three discriminant functions, built from parameters derived from the histogram and the co-occurrence matrix. These functions were calculated by means of a stepwise discriminant analysis on 79 samples from a training set. Results provided a correct classification of 96.8% on an independent test set of 251 samples labeled manually. Regression analysis showed a good agreement between automatic and manual methods. A reliable and easy to implement method has been developed to provide an automatic method for quantifying microscopy images of lung histological studies. Results showed similar accuracy to that provided by an expert, while allowing analyzing a much larger number of fields in a repeatable way.
2008 International Society for Advancement of Cytometry.