A SYSTEM FOR ACUTE LEUKEMIA CELLS SEGMENTATION AND CLASSIFICATION | ||||
| International Journal of Intelligent Computing and Information Sciences | ||||
| Article 7, Volume 16, Issue 4, October 2016, Page 79-87 PDF (1.56 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ijicis.2016.19829 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| R. Mohammed1; O. Nomir1; I. I. Khalifa2; T. Hamza2 | ||||
| 1Computer Science Department, faculty of computer and informatics Mansoura University , Egypt | ||||
| 2Computer Science Department, faculty of computer and informatics | ||||
| Abstract | ||||
| This research paper presents a system for the acute leukemia blast cells segmentation and classification. The research objective is to generate the features characterizing normal and infected cells. The proposed system consists of one segmentation method and one classification method of acute leukemia. The features extracted from the cell and adopted features are used as the input signals to the Multi Layer Perception (MLP) neural network classifier. The experimental results show that our proposed system is robust and effective in identifying acute leukemia blast cells. | ||||
| Keywords | ||||
| mage Segmentation; ALL; RGB; C-Y color model; features extraction; MLP | ||||
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