HIGH-THROUGHPUT MICROSCOPE-BASED DEVICE DEVELOPMENT FOR ANALYSIS OF PERIPHERAL BLOOD SMEARS FOR ANEMIA SCREENING

The conventional method of screening for anemia requires the pathologist or technician to manually focus the microscope and examine one slide at a time, making the process tedious, especially in health emergencies. Therefore, the research work aims to design and develop an automated high-throughput optical digital microscope-based device for scanning and capturing blood smear images using Laplacian based auto focusing algorithm of 10 peripheral blood smear slides sequentially in a batch focusing on a particular field of view at an objective lens magnification of 40x. The acquired images are segmented using YOLO(You Only Look Once) algorithm to analyze the morphology of red blood cells (RBC) to screen for anemia. with a multilayer perceptron (MLP) classifier images are categorized into macrocytic, microcytic, normocytic subclasses and normal class. The trained model is embedded in a smartphone application to map classified anemic images by geographic location, creating anemia clusters.