Background: OvaSpec is a new, fully automated, vision-based instrument for assessing the quantity (concentration) and quality (embryonation percentage) of Trichuris suis parasite eggs in liquid suspension. The eggs constitute the active pharmaceutical ingredient in a medicinal drug for the treatment of immune-mediated diseases such as Crohn׳s disease, ulcerative colitis, and multiple sclerosis.
Methods: This paper describes the development of an automated microscopy technology, including methodological challenges and design decisions of relevance for the future development of comparable vision-based instruments. Morphological properties are used to distinguish eggs from impurities and two features of the egg contents under brightfield and darkfield illumination are used in a statistical classification to distinguish eggs with undifferentiated contents (non-embryonated eggs) from eggs with fully developed larvae inside (embryonated eggs).
Results: For assessment of the instrument׳s performance, six egg suspensions of varying quality were used to generate a dataset of unseen images. Subsequently, annotation of the detected eggs and impurities revealed a high agreement with the manual, image-based assessments for both concentration and embryonation percentage (both error rates <1.0%). Similarly, a strong correlation was demonstrated in a final, blinded comparison with traditional microscopic assessments performed by an experienced laboratory technician.
Conclusions: The present study demonstrates the applicability of computer vision in the production, analysis, and quality control of T. suis eggs used as an active pharmaceutical ingredient for the treatment of autoimmune diseases.
Keywords: Computer vision; Concentration; Darkfield microscopy; Embryonation percentage; Image analysis; Parasite egg classification; Trichuris suis eggs.
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