Development of an Affordable Approach for Counting Red Blood Cells Based on the Software Image Processing of Microscopy Images
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Blood Analysis, Computer Vision, Image Processing, Red Blood Cells
Abstract
Red blood cells make up 99% of the blood cells, and their assessment is a key factor in the medical diagnosis of diseases. There are many blood cell counting techniques that evolved over the years to include traditional techniques in addition to modern automated techniques. The traditional method used in hospital laboratories includes manual counting and sorting of blood cells using a hemocytometer and microscope, which are considered monotonous, laborious, and time consuming methods, in addition to the inaccuracy of their results caused by human errors. Red cell counting techniques are developed with the advent of the Automated Blood Analyzer method, which is very expensive and cannot be afforded in all laboratories, especially those positioned in remote areas of the third world countries. This paper introduces the idea of developing an affordable approach in the form of a MATLAB-based software application, which is capable of using image processing techniques to detect red blood cell counts in blood samples. The application uses samples of blood microscopic images taken using a normal mobile camera. The testing of this approach has shown slight improvement in the time and accuracy of the analysis compared to manual red blood cell analysis.
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References
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