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Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and extreme learning machine

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Main Authors: Muhammad Khusairi, Osman, Mohd Yusof, Mashor, Prof. Dr., Hasnan, Jaafar, Assoc. Prof. Dr.
Other Authors: khusairi@ppinang.uitm.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2011
Subjects:
Affine moment invariants
Extreme Learning Machine
Neural network
Tissue sections
Tuberculosis bacilli detection
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/15102
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spelling 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)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Affine moment invariants
Extreme Learning Machine
Neural network
Tissue sections
Tuberculosis bacilli detection
spellingShingle 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
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 khusairi@ppinang.uitm.edu.my
author_facet 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
_version_ 1643790838038265856
score 13.18916

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