Proposal of a Medical Algorithm Based on the Application of Digital Image Processing and Visual Communication Techniques

Blood tests help detect various types of diseases, where the erythrocytes count (RBC) and leukocytes (WBC) can use automatic and/or manual methodologies. The evaluation of RBC and WBC has a direct impact on the diagnosis of anemia, leukemia, viral, parasitic and viral infections. Given the importance and wide applicability of the Watershed Transform (WT) and Morphological Operations (MO), they can segment medical images to increase the efficiency and reliability of medical diagnostics. This study uses a WT-MO algorithm for segmentation, detection, and counting of blood cells that attend the criteria of efficiency and reliability. This methodology may be the first step in making blood tests more accessible to people from developing and underdeveloped countries. The WT-MO algorithm has been benchmarked using 30 microscopy images of a blood smear. The WT-MO algorithm results presented high accuracy (93%). The simulations of the algorithm executed in different hardware platforms presented average simulation and processing time with less than 3 seconds per sample. Therefore, the WT-MO based algorithm is accurate, reliable and a low-cost technique, which can be applied as a third methodology to perform the laboratory tests and to speed up further medical diagnostic.