| International Journal of Computer Science and Security | |
| Automated Protocol for Counting Malaria Parasites (P. falciparum) from Digital Microscopic Image Based on L*a*b* Colour Model and K-Means Clustering | |
| A. G. Akyea1  J. N. Boampong1  C. L. Y. Amuah1  P. Osei-Wusu Adueming1  J. Opoku-Ansah1  B. Anderson1  J. M. Eghan1  | |
| [1] $$ | |
| 关键词: Malaria Parasites; Image processing; Segmentation; K-means; cluster; L*a*b* colour model.; | |
| DOI : | |
| 来源: Computer Science and Security | |
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【 摘 要 】
Basis for malaria parasites diagnosis in most hospitals and clinics, especially in developing countries, which is manually done, is strenuous and time-consuming. In this paper, we present an automated protocol for counting malaria parasites (P. falciparum) from digital microscopic red blood cells (RBCs) mages based on L*a*b* colour model and K-Means clustering algorithm using Matlab. This method is device-independent, perceptually uniform and approximates human vision. An image slide of size 300 x 300 x 3 pixels of RBCs with malaria parasites has been counted in less than 10 seconds using a computer with 64-bit Intel (R) Celeron (R) Central Processing Unit and processing speed of 2.20 GHz. The digital counts have a good correlation with the manual counts. This automated protocol has the potential of providing fast, accurate and objective detection information for proper clinical management of patients.
【 授权许可】
Unknown
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO201912040511555ZK.pdf | 2824KB |
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