Estimating Malaria Parasitaemia from Blood Smear Images

Abstract

A technique is proposed for estimating parasitaemia from blood smear images by extracting healthy and parasite infected red blood cells. The developed approach accounts for uncertain imaging conditions due to microscope settings as well as the quality of the blood smear preparation. The solution is based on a multi-stage estimation process with minimal prior knowledge starting from a model representation of red blood cells. Based on pattern matching with parameter optimisation and cross-validation against the expected biological characteristics, red blood cells are determined. In a final stage, the parasitaemia measure is carried out by partitioning the uninfected and infected cells using an unsupervised and in comparison a training-based technique. Finally, the obtained estimates were analysed with respect to manually acquired results from professionals. Red blood cells detection resulted in precision and recall rates of 80-88% and 92-98%, respectively. By using a training-based method, the precision and recall rates were improved to 92% and 95%, respectively