Methodology of high accuracy, sensitivity and specificity in the counts of erythrocytes and leukocytes in blood smear images

The evaluation of human blood is an important diagnostic method for the detection of diseases. The analysis of the erythrocytes contained in the blood contributes to the detection of anemia and leukemia, whereas the leukocyte analysis allows the diagnosis of inflammation and/or infections. The blood is analyzed through of the complete blood count test (CBC), which is dependent on automated and/or manual methodologies. The dependence of medical areas on new technologies leads the present study to the goal of developing an image segmentation algorithm that meets the criteria of efficiency and reliability for detection and counting of blood cells. The algorithm was developed through the Matlab software, being the image processing methodology based on the union of the Watershed transform and Morphological Operations, originating the WT-MO methodology. For the simulations, 30 blood smear images containing erythrocytes and leukocytes were used in a non-pathological state. The results showed that the WT-MO methodology presents high sensitivity (99%), specificity (96%) and accuracy (98,3%) when compared with the manual methodology. Therefore, the WT-MO methodology is an accurate, reliable and low-cost technique and can be applied as a third more accessible methodology to perform of the complete blood count test (CBC) in populations of underdeveloped and developing countries1407990BTSym 2018 : Proceedings of the 4th Brazilian Technology Symposium (BTSym'18)2018Blood cells Watershed transform Morphological operations Blood smear Image processing Algorith

A comparative study between methodologies based on the hough transform and watershed transform on the blood cell count

It is increasingly common to use engineering techniques in the areas of health, in order to solve simple problems or even create new diagnostic methods. In the last decade, the Hough Transform has been widely used as a tool for segmentation of blood smear images for the purpose of counting blood cells. However, it is noted that the Watershed transform has been applied to perform the same function. Based on this, a methodology based on the Hough Transform was created, aiming to perform the detection and counting of erythrocytes and leukocytes and verify the applicability of the methodology when compared to others. The study was conducted based on the determination of accuracy and simulations performed on different hardware platforms and subsequent comparison with the WT-MO methodology. The results demonstrated that both methodologies are able to perform the task of detection and counting of blood cells in digital images of blood smear. However, the methodology based on the Watershed Transform best meets the criteria of speed and reliability (counts), which are indispensable to medical laboratory routine1406578BTSym 2018 : proceedings of the 4th brazilian technology symposium (BTSym'18)201