#152: Image analysis of blood slides for automatic malaria diagnosis


M. Poostchi, I. Ersoy, A. Bansal, K. Palaniappan, S. Antani, S. Jaeger, and G. Thoma

NIH-IEEE Strategic Conference on Healthcare Innovations and Point-of-Care Technologies for Precision Medicine (HI-POCT), 2015

malaria, biomedical, image analysis

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Abstract

Malaria is a serious global health problem, claiming the lives of 450,000 children per year. A fast and reliable test for diagnosing malaria would be a promising approach to fight this disease. We present an automatic system for diagnosing and quantifying a malaria infection in cultured red blood cells on thin films, using image processing techniques. We measure an average error of 1.8% by comparing the true frequency of infected cells with the automatically computed infection frequency, which encourages applying our technique for malaria diagnosis in the field.