Methodology

Computer vision for microscopy diagnosis of malaria

F Boray Tek¹ , Andrew G Dempster² and Izzet Kale¹

¹  Applied DSP & VLSI Research Group, University of Westminster, London, UK

²  School of Surveying & Spatial Information Systems, University of New South Wales, Sydney, Australia

author email corresponding author email

Malaria Journal 2009, 8:153doi:10.1186/1475-2875-8-153

Published:	13 July 2009

Abstract

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.