Detection of tuberculosis bacilli in tissue slide images using HMLP network trained by Extreme Learning Machine
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 o...
| الحاوية / القاعدة: | Elektronika ir Elektrotechnika |
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| المؤلف الرئيسي: | |
| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Kauno Technologijos Universitetas
2012
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| الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859750877&doi=10.5755%2fj01.eee.120.4.1456&partnerID=40&md5=55381beb82814f44f94cd26f371499b0 |
| الملخص: | 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). |
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| تدمد: | 13921215 |
| DOI: | 10.5755/j01.eee.120.4.1456 |