Detection of Tuberculosis Bacilli in Tissue Slide Images using HMLP Network Trained by Extreme Learning Machine

  • M. K. Osman Universiti Teknologi MARA
  • M. Y. Mashor Universiti Malaysia Perlis
  • H. Jaafar Universiti Sains Malaysia

Abstract

This paper proposes an automated detection of tuberculosis bacilli in Ziehl-Neelsen-stained tissue slides using image processing and neural network. Image segmentation using CY-based colour filter and k-mean clustering procedure is used to separate objects of interest from the background. A number of geometrical features are then extracted from the segmented images. A recent training algorithm called Extreme Learning Machine (ELM) is modified to train a hybrid multilayered perceptron network (HMLP) for the classification task. The results indicate that the performance of HMLP-ELM network is comparable to the previously proposed methods and offers a fast training time with no designing parameter required. Ill. 6, bibl. 15, tabl. 1 (in English; abstracts in English and Lithuanian).

DOI: http://dx.doi.org/10.5755/j01.eee.120.4.1456

Published
2012-04-03
Section
AUTOMATION, ROBOTICS