Automated segmentation of blood cells in Giemsa stained digitized thin blood films

Background Assessment of erythrocytes and leucocytes in thin blood films can be used as an inexpensive diagnostic aid in a series of disease states, e.g. infections, anemia and hematological malignancies. Manual counting of cells is still considered the gold standard for example to establish the level of parasitemia in malaria. However, manual cell counting is time consuming and subject to variability [1]. We here propose an image analysis method that is a combination of adaptive histogram thresholds and morphologic characteristics for the segmentation of red blood cells (RBCs) and white blood cells (WBCs) in digitized thin blood films. The method is implemented on a virtual microscopy platform, the Webmicroscope [2].