Image Processing Reference
tion algorithm. Based on the experimental results, these procedures have demonstrated high
accuracies, and these models appear successful at predicting the healthy and distorted cells
present in blood from a person with sickle-cell anemia. I calculated the performance of the
models, using three statistical measures: classification accuracy, sensitivity, and specificity. As
a result, I have concluded that this algorithm has correctly segmented and classified about
99.98% of all input cells, which may have contributed to the improved diagnosis of sickle-cell
anemia. The experimental results have shown that the effectiveness reaches to 96.9% in the
case of applying an NN and 92.9% when using a C&R tree. Therefore, the proposed algorithm
is very effective for detecting benign and distorted RBCs, and the NN is more efficient than a
C&R tree for testing the quality of the detection algorithm.
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