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The Discrimination of Red Blood Cells Infected by Hereditary Hemolytic Anemia | ||
| AL-Rafidain Journal of Computer Sciences and Mathematics | ||
| Article 5, Volume 10, Issue 1, 2013, Pages 65-78 PDF (793.79 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/csmj.2013.163425 | ||
| Authors | ||
| Ghayda A.A. Al-Talib; Hesham H. Mohameed | ||
| College of Computer Sciences and Mathematics University of Mosul, Mosul, Iraq | ||
| Abstract | ||
| This paper presents a medical application based on digital image processing and Artificial Neural Network (ANN), which can recognize three types of Hereditary Hemolytic Anemia (HHA) that affect the Red Blood Cells (RBCs) and change their shape. Three Feed Forward Back Propagation Learning (FFBBL) Neural Networks are used in hierarchical approach to achieve this goal. The essence of this research is to segment each Red Blood Cell in a separate image and then extract some interesting features from each image in order to present them to the neural networks. The latter will, in turn, take the decision whether the RBC is infected or not. The results showed a recognition rate 92.38 %. | ||
| Keywords | ||
| Hereditary Hemolytic Anemia; red blood cells; NN | ||
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