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Eggs from the small, intestinal pig whipworm Trichuris suis constitute the active pharmaceutical ingredient in a novel type of medicine for chronic autoimmune diseases like Crohn's disease. The pharmaceutical potency of such an egg suspension can be assessed by microscopic inspection, as only eggs containing a viable, infective larva provoke the wanted immune reaction. Thus, a precise and objective estimate of the concentration of infective eggs is crucial for dosing the new medicine. In this paper, a vision-based method for detecting and classifying T. suis parasite eggs is described. The detection is based on matched filters and the classification is done using linear and quadratic discriminant analysis on a set of biologically inspired features, including the autocorrelation-based longitudinal anisotropy and the mean scattering intensity under dark field illumination. Despite the presence of impurities and overlapping eggs, the proposed method achieves cross-validated classification rates around 93%.