Abstract
Automated separation of blood cells from the background in thin blood film samples is of importance in the process of cell counting and as a first step in image analysis of red and white blood cells morphology.
Highlights
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
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
RBCs were manually annotated in 30 fields of views per thin blood film and WBCs were annotated in the entire data set (Table 1)
Summary
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. 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]
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