Automatic System for Plasmodium Species Identification from Microscopic Images of Blood-Smear Samples

J Healthc Inform Res. 2017 Nov 6;1(2):231-259. doi: 10.1007/s41666-017-0009-2. eCollection 2017 Dec.

Abstract

Malaria spreads rapidly in a particular time of the year, and it becomes impossible to arrange sufficient number of pathologists and physician at that time, especially in remote places of the developing nations. Thus, low-cost pathological equipment, which can automatically identify and classify the type of malarial parasites from the microscopic images of blood samples, will be of great help for diagnosis and treatment of malaria. The proposed system detects malarial parasites from the microscopic images of blood samples and also categorizes them based on shape, size and texture. To capture different field images of the same sample, a fully automatic slide movement system is devised to control the slide movement under the "objective lens" of the microscope. The sensitivity and specificity of the system are found to be 91.42 and 87.36% respectively. The system has the potential to a powerful supporting tool for telemedicine with very simple operational instructions.

Keywords: Erosion and dilation; Gradient operator; HSI color model; Histogram; Level set; Malaria parasites; Plasmodium species; Random forest.