In this paper, we propose a low-cost technological model for optimizing the detection process of leukemia using digital microscopy. The model is targeted to be used in remote areas in developing countries where availability of resources is an issue. This model applies the canny algorithm on a bank of images of normal and abnormal microscopic cells. The proposed model includes the capture, digitization, and analysis of microscopic samples, Fives phases are included in this model: 1. Data collection; 2. Data capture; 3. Image processing; 4. Cell classification; 5. Display of results. The model was preliminary validated with five blood samples from three men and two women in different age categories. All these samples were validated by the Head of Clinical Pathology at a public hospital in Callao, Lima, Peru. The results showed that a 90.5% effectiveness rate of white blood cell identification was obtained. This results aims to provide an additional and accurate tool to detection of potential leukemia.