Sickle Blood Cell Detection Based on Image
Segmentation
Red blood cells have a vital role in human health. Red blood cells have a circular
shape and a concave surface and exchange the gasses between the inside and outside of the body. However, at times, these normally round cells become sickle shaped, which is an indication of sickle cell disease.
This paper introduces a unique approach to detect sickle blood cells in blood
samples using image segmentation and shape detection. This method is based on
calculating the max axis and min axis of the cell. The form factor is computed using these properties to determine whether the cell is sickle or not. This method is 90 percent more accurate than the existing method.
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