Image Processing Reference
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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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