title: Image classification of unlabeled malaria parasites in red blood cells.
abstract: This paper presents a method to detect unlabeled malaria parasites in red blood cells. The current "gold standard" for malaria diagnosis is microscopic examination of thick blood smear, a time consuming process requiring extensive training. Our goal is to develop an automate process to identify malaria infected red blood cells. Major issues in automated analysis of microscopy images of unstained blood smears include overlapping cells and oddly shaped cells. Our approach creates robust templates to detect infected and uninfected red cells. Histogram of Oriented Gradients (HOGs) features are extracted from templates and used to train a classifier offline. Next, the ViolaJones object detection framework is applied to detect infected and uninfected red cells and the image background. Results show our approach out-performs classification approaches with PCA features by 50% and cell detection algorithms applying Hough transforms by 24%. Majority of related work are designed to automatically detect stained parasites in blood smears where the cells are fixed. Although it is more challenging to design algorithms for unstained parasites, our methods will allow analysis of parasite progression in live cells under different drug treatments.
authors.lastname: Zheng Zhang
authors.forename: L L Sharon
authors.initials: LL
authors.lastname: Ong
authors.lastname: Kong Fang
authors.forename: Athul
authors.initials: A
authors.lastname: Matthew
authors.forename: Justin
authors.initials: J
authors.lastname: Dauwels
authors.lastname: Ming Dao
authors.forename: Harry
authors.initials: H
authors.lastname: Asada
mesh_terms: D000465:Algorithms; D000818:Animals; D019992:Databases as Topic; D004912:Erythrocytes / Q000469:parasitology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008288:Malaria / Q000469:parasitology; D010271:Parasites / Q000166:cytology*; D025341:Principal Component Analysis; D013194:Staining and Labeling