Malaria, caused by a blood parasite of the genus plasmodium, kills millions of people each year. According to the World Health Organization, the standard for malaria diagnosis is microscopic examination of a stained blood film. We have developed a two-stage algorithm for the automatic detection of plasmodia in thick blood films. The focus of the first stage is on high detection sensitivity while accepting high numbers of false-positive detections per image. The second stage reduces the number of false-positive detections to an acceptable level while maintaining the detection sensitivity of the first stage. The algorithm can detect plasmodia at a sensitivity of 0.97 with a mean number of 0.8 false-positive detections per image. Our results indicate that the proposed algorithm is suitable for the development of an automated microscope for computer-aided malaria screening.
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