Published Paper Details:

Dengue fever is a major problem in many developing countries, including India. For dengue patient monitoring, platelet count is vital to ensure early treatment in order to prevent disease complications. In primary health care centers platelet counting is typically performed manually, which is labor intensive and requires an experienced laboratory technician. Another method used, is the Advia hematology analyzer, which is very expensive, not affordable for rural and remote areas. To address present day challenges, developed an automated approach for the detection of platelet, along with the symptoms helps in assisting the detection of dengue. The technology is based on microscopic images derived from blood smears obtained using a digitalized camera attached to a microscope. Image processing and segmentation techniques are applied to estimate the platelet count from these blood slides. To further improve the accuracy of the results, an analysis of symptoms present in the patient is used in conjunction with the platelet analysis. Proposed vector based method for screening the samples. The classifier performance is evaluated with the sensitivity and specificity values. The results of platelet counts obtained from other platelet counting machines and manually are compared. The reported tool helps in the modernization of pathology laboratory into digital, as well it speedup the mass screening.