Detection of tuberculosis bacilli in tissue slide images using HMLP network trained by Extreme Learning Machine

• Published in: Elektronika ir Elektrotechnika
• Main Author: Osman M.K.; Mashor M.Y.; Jaafar H.
• Format: Article
• Language: English
• Published: Kauno Technologijos Universitetas 2012
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859750877&doi=10.5755%2fj01.eee.120.4.1456&partnerID=40&md5=55381beb82814f44f94cd26f371499b0

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).