Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine
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Institute of Electrical and Electronics Engineers (IEEE)
2011
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my.unimap-151022011-10-27T07:47:25Z Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine Muhammad Khusairi, Osman Mohd Yusof, Mashor, Prof. Dr. Hasnan, Jaafar, Assoc. Prof. Dr. khusairi@ppinang.uitm.edu.my Affine moment invariants Extreme Learning Machine Neural network Tissue sections Tuberculosis bacilli detection Link to publisher's homepage at http://ieeexplore.ieee.org/ This paper describes an approach to automate the detection and classification of tuberculosis (TB) bacilli in tissue section using image processing technique and feedforward neural network trained by Extreme Learning Machine. It aims to assist pathologists in TB diagnosis and give an alternative to the conventional manual screening process, which is time-consuming and labour-intensive. Images are captured from Ziehl-Neelsen (ZN) stained tissue slides using light microscope as it is commonly used approach for diagnosis of TB. Then colour image segmentation is used to locate the regions correspond to the bacilli. After that, affine moment invariants are extracted to represent the segmented regions. These features are invariant under rotation, scale and translation, thus useful to represent the bacilli. Finally, a single layer feedforward neural network (SLFNN) trained by Extreme Learning Machine (ELM) is used to detect and classify the features into three classes: 'TB', 'overlapped TB' and 'non-TB'. The results indicate that the ELM gives acceptable classification performance with shorter training period compared to the standard backpropagation training algorithms. 2011-10-27T07:47:25Z 2011-10-27T07:47:25Z 2011-03-04 Working Paper p. 232-236 978-1-6128-4414-5 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5759878 http://hdl.handle.net/123456789/15102 en Proceeding of the 7th International Colloquium on Signal Processing and Its Applications (CSPA 2011) Institute of Electrical and Electronics Engineers (IEEE) |
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Affine moment invariants Extreme Learning Machine Neural network Tissue sections Tuberculosis bacilli detection |
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Affine moment invariants Extreme Learning Machine Neural network Tissue sections Tuberculosis bacilli detection Muhammad Khusairi, Osman Mohd Yusof, Mashor, Prof. Dr. Hasnan, Jaafar, Assoc. Prof. Dr. Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine |
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Link to publisher's homepage at http://ieeexplore.ieee.org/ |
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khusairi@ppinang.uitm.edu.my |
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khusairi@ppinang.uitm.edu.my Muhammad Khusairi, Osman Mohd Yusof, Mashor, Prof. Dr. Hasnan, Jaafar, Assoc. Prof. Dr. |
format |
Working Paper |
author |
Muhammad Khusairi, Osman Mohd Yusof, Mashor, Prof. Dr. Hasnan, Jaafar, Assoc. Prof. Dr. |
author_sort |
Muhammad Khusairi, Osman |
title |
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine |
title_short |
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine |
title_full |
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine |
title_fullStr |
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine |
title_full_unstemmed |
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine |
title_sort |
tuberculosis bacilli detection in ziehl-neelsen-stained tissue using affine moment invariants and extreme learning machine |
publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
publishDate |
2011 |
url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/15102 |
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1643790838038265856 |
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13.18916 |