Automated complete blood count using image processing

• Main Authors: Adorable, Paolo Gabriel G., Galman, Roberto SP., Legaspi, Fernando Luis M., Ocampo, Peter Ryan H.
• Format: text
• Language: English
• Published: Animo Repository 2006
• Subjects: Blood cells > Automation; Blood cell count > Automation; Cytodiagnosis > Automation; Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/14263
• Institution: De La Salle University

Blood count is an indicative method of assessing the patient's health through the cells present in the blood. Blood consists of three major types of cells namely, erthrocytes or red blood cells (RBC), leukocytes or white blood cells (WBC) and platelets. The abnormally low or abnormally high count of either the erythrocytes or leukocytes is an indication of a disease or an infection. There are two approaches in blood count namely the manual and electronic method. The manual method is the preferred method because of its accuracy in cell classification and identification however, it is tedious, time-consuming and prone to human error. The output of the research is a prototype that automates RBC and WBC count. Using image processing, the computer performs the count eliminating the introduction of human errors such as subjectivity and erroneous counting. Images are acquired through a microscope camera connected to the computer via the USB port. The input to the system is pre-treated blood sample in the hemocytometer placed on the microscope stage. The GUI allows the user to view the image, capture the image, control the stage movement, perform the image processing & cell count, and display the result. Automated Complete Blood Count using the Image Processing performs cell count of RBC and WBC with cell detection rate of 92.7% and 97.5% respectively.