Probabilistic prediction of malaria using morphological and textural information

The objective of this paper is to introduce a computer assisted prediction of malaria infection particularly Plasmodium vivax based on the morphological and textural information. Here erythrocytes have been segmented from light microscopic images of peripheral blood smear using marker controlled watershed followed by pre-processing. Thereafter texture and morphology of erythrocytes are extracted using geometrical and Haralick texture measure. Finally statistically significant features are fitted with multivariate regression model. This predictive model is good fitted (-2 Log Likelihood = 24.636 and Chi-Square = 820.949) and it gives 88.77 % prediction accuracy.