title: Investigation of a novel approach to scoring Giemsa-stained malaria-infected thin blood films.
abstract: Daily assessment of the percentage of erythrocytes that are infected ('percent-parasitaemia') across a time-course is a necessary step in many experimental studies of malaria, but represents a time-consuming and unpopular task among researchers. The most common method is extensive microscopic examination of Giemsa-stained thin blood-films. This study explored a method for the assessment of percent-parasitaemia that does not require extended periods of microscopy and results in a descriptive and permanent record of parasitaemia data that is highly amenable to subsequent 'data-mining'. Digital photography was utilized in conjunction with a basic purpose-written computer programme to test the viability of the concept. Partial automation of the determination of percent parasitaemia was then explored, resulting in the successful customization of commercially available broad-spectrum image analysis software towards this aim. Lastly, automated discrimination between infected and uninfected RBCs based on analysis of digital parameters of individual cell images was explored in an effort to completely automate the calculation of an accurate percent-parasitaemia.
authors.affiliation: Burnet Institute, Austin Hospital campus, Studley Road, Heidelberg, Melbourne, 3084, Australia. o.proudfoot@burnet.edu.au
authors.forename: Owen
authors.initials: O
authors.lastname: Proudfoot
authors.forename: Nathan
authors.initials: N
authors.lastname: Drew
authors.forename: Anja
authors.initials: A
authors.lastname: Scholzen
authors.forename: Sue
authors.initials: S
authors.lastname: Xiang
authors.forename: Magdalena
authors.initials: M
authors.lastname: Plebanski
mesh_terms: D000818:Animals; D001331:Automation; D001769:Blood / Q000469:parasitology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008288:Malaria / Q000175:diagnosis*; D018512:Parasitemia / Q000175:diagnosis*; D010274:Parasitology / Q000379:methods*