Detecting and Segmenting White Blood Cells in Microscopy Images of Thin Blood Smears

A malarial infection is diagnosed and monitored by screening microscope images of blood smears for parasite-infected red blood cells. Millions of blood slides are manually screened for parasites every year, which is a tedious and error-prone process, and which largely depends on the expertise of the microscopists. We have developed a software to perform this task on a smartphone, using machine learning and image analysis methods for counting infected red blood cells automatically. The method we implemented first needs to detect and segment red blood cells. However, the presence of white blood cells (WBCs) contaminates the red blood cell detection and segmentation process because WBCs can be miscounted as red blood cells by automatic cell detection methods. As a result,…