Detecting distorted and benign blood cells using the Hough transform based on neural networks and decision trees
Hany A. Elsalamony Mathematics Department, Faculty of Science, Helwan University, Cairo, Egypt
Abstract
Sickle-cell anemia is one of the most important types of anemia. This paper presents an algorithm for detecting blood cells characteristic of sickle-cell anemia. First, I discuss the construction of an algorithm that can be used to detect and count benign or distorted red blood cells (RBCs) in a microscopic colored image, even if those cells are hidden or overlapped. Second, I explain the process for checking and analyzing the constructed RBC data by applying two important techniques in data mining: the neural network ...
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