Fatin Izzwani, Azman and Kamarul Hawari, Ghazali and Rosyati, Hamid and Noor Amira Syuhada , Mahamad Salleh (2014) Detection Technique of Squamous Epithelial Cells in Sputum Slide Images using Image Processing Analysis. In: Proceeding of International Conference on Electrical Engineering, Computer Science and Informatics (EECSI 2014) , 20-21 August 2014 , Yogyakarta, Indonesia. pp. 400-404..
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Detection Technique of Squamous Epithelial Cells in Sputum Slide Images using Image Processing Analysis.pdf - Published Version Download (1MB) | Preview |
Abstract
A good quality sputum is important to detect diseases. The presence of squamous epithelial cells (SEC) in sputum slide images is important to determine the quality of sputum. The presence of overlapping SEC in sputum slide images causes the process become complicated and tedious. Therefore this paper discusses on technique of detection and summation for Squamous Epithelial Cell (SEC) in sputum slide image. We addressed the detection problem by combining K-means and color thresholding algorithm. The design of aided system is evaluated using 200 images and the proposed technique is capable to detect and count each SEC from overlapping SEC image. Total of 200 images were clustered to 10 groups, labelled as Group Cell 1 to group Cell 10 that correspond to the number of cells in the image. Therefore, each group will contain 20 images. The accuracy of the algorithm to detect SEC was also measured, and results show that in 91% which provides a correct SEC detection and summation.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | Squamous Epithelial Cell (SEC); K-means algorithm; color thresholding. |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Faculty/Division: | Faculty of Electrical & Electronic Engineering |
Depositing User: | Mrs. Neng Sury Sulaiman |
Date Deposited: | 07 Dec 2015 07:40 |
Last Modified: | 21 Feb 2018 04:34 |
URI: | http://umpir.ump.edu.my/id/eprint/9428 |
Download Statistic: | View Download Statistics |
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