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Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks

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Main Authors: Aimi, Abdul Nasir, Mohd Yusoff Mashor, Prof. Dr., Rosline, Hassan
Format: Article
Language:English
Published: Zarqa University, Jordan 2014
Subjects:
Acute leukaemia cells
Feature extraction
Classification
Multilayer perceptron neural network
Simplified fuzzy ARTMAP neural network
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/32487
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spelling my.unimap-324872014-03-10T09:05:54Z Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks Aimi, Abdul Nasir Mohd Yusoff Mashor, Prof. Dr. Rosline, Hassan Acute leukaemia cells Feature extraction Classification Multilayer perceptron neural network Simplified fuzzy ARTMAP neural network Link to publisher's homepage at http://iajit.org Leukaemia is a cancer of blood that causes more death than any other cancers among children and young adults under the age of 20. This disease can be cured if it is detected and treated at the early stage. Based on this argument, the requirement for fast analysis of blood cells for leukaemia is of paramount importance in the healthcare industry. This paper presents the classification of White Blood Cells (WBC) inside the Acute Lymphoblastic Leukaemia (ALL) and Acute Myelogenous Leukaemia blood samples by using the Multilayer Perceptron (MLP) and Simplified Fuzzy ARTMAP (SFAM) neural networks. Here, the WBC will be classified as lymphoblast, myeloblast and normal cell for the purpose of categorization of acute leukaemia types. Two different training algorithms namely Levenberg-Marquardt and Bayesian Regulation algorithms have been employed to train the MLP network. There are a total of 42 input features that consist of the size, shape and colour based features, have been extracted from the segmented WBCs, and used as the neural network inputs for the classification process. The classification results indicating that all networks have produced good classification performance for the overall proposed features. However, the MLP network trained by Bayesian Regulation algorithm has produced the best classification performance with testing accuracy of 95.70% for the overall proposed features. Thus, the results significantly demonstrate the suitability of the proposed features and classification using MLP and SFAM networks for classifying the acute leukaemia cells in blood sample. 2014-03-10T09:05:54Z 2014-03-10T09:05:54Z 2013-07 Article International Arab Journal of Information Technology, vol.10 (4), 2013, pages 356-364 1683-3198 http://dspace.unimap.edu.my:80/dspace/handle/123456789/32487 http://www.ccis2k.org/iajit/index.php?option=com_content&task=blogcategory&id=87&Itemid=355 en Zarqa University, Jordan
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 Acute leukaemia cells
Feature extraction
Classification
Multilayer perceptron neural network
Simplified fuzzy ARTMAP neural network
spellingShingle Acute leukaemia cells
Feature extraction
Classification
Multilayer perceptron neural network
Simplified fuzzy ARTMAP neural network
Aimi, Abdul Nasir
Mohd Yusoff Mashor, Prof. Dr.
Rosline, Hassan
Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks
description Link to publisher's homepage at http://iajit.org
format Article
author Aimi, Abdul Nasir
Mohd Yusoff Mashor, Prof. Dr.
Rosline, Hassan
author_facet Aimi, Abdul Nasir
Mohd Yusoff Mashor, Prof. Dr.
Rosline, Hassan
author_sort Aimi, Abdul Nasir
title Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks
title_short Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks
title_full Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks
title_fullStr Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks
title_full_unstemmed Classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy ARTMAP neural networks
title_sort classification of acute leukaemia cells using multilayer perceptron and simplified fuzzy artmap neural networks
publisher Zarqa University, Jordan
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/32487
_version_ 1643796920474271744
score 13.214268

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