Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique
International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia.
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Universiti Malaysia Perlis (UniMAP)
2012
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my.unimap-216232014-06-27T09:48:53Z Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique Aimi Salihah, Abdul Nasir Mohd Yusoff, Mashor, Prof. Dr. Azian Azamimi, Abdullah aimi_salihah@yahoo.com Acute leukemia Contrast enhancements Acute Myelogenous Leukemia (AML) Leukaemia Blood cancer Colour image segmentation International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia. Contrast enhancement and image segmentation techniques have fast becoming popular for computer vision and image processing area in the last few decades. In this paper, the combination between contrast enhancement and segmentation were used in order to obtain a fully segmented abnormal white blood cell (blast). The combinations of contrast enhancement that had been used were partial contrast and bright stretching techniques. The bright stretching technique enhanced the area of blast in acute leukaemia images to ease the segmentation process. The proposed segmentation technique based on HSI (Hue, Saturation, Intensity) colour space has successfully segmented the acute leukaemia images while preserving significant features. The combination between two contrast enhancements has good effect on improving the accuracy of blast segmentation. Hence, the resultant images would become useful to Hematologists for further analysis of acute leukaemia. 2012-11-05T09:29:55Z 2012-11-05T09:29:55Z 2010-10-16 Working Paper 978-967-5760-03-7 http://hdl.handle.net/123456789/21623 en Proceedings of the International Postgraduate Conference on Engineering (IPCE 2010) Universiti Malaysia Perlis (UniMAP) Centre for Graduate Studies |
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Acute leukemia Contrast enhancements Acute Myelogenous Leukemia (AML) Leukaemia Blood cancer Colour image segmentation |
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Acute leukemia Contrast enhancements Acute Myelogenous Leukemia (AML) Leukaemia Blood cancer Colour image segmentation Aimi Salihah, Abdul Nasir Mohd Yusoff, Mashor, Prof. Dr. Azian Azamimi, Abdullah Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique |
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International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia. |
author2 |
aimi_salihah@yahoo.com |
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aimi_salihah@yahoo.com Aimi Salihah, Abdul Nasir Mohd Yusoff, Mashor, Prof. Dr. Azian Azamimi, Abdullah |
format |
Working Paper |
author |
Aimi Salihah, Abdul Nasir Mohd Yusoff, Mashor, Prof. Dr. Azian Azamimi, Abdullah |
author_sort |
Aimi Salihah, Abdul Nasir |
title |
Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique |
title_short |
Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique |
title_full |
Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique |
title_fullStr |
Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique |
title_full_unstemmed |
Improving blast segmentation of acute myelogenous leukaemia (AML) images using bright stretching technique |
title_sort |
improving blast segmentation of acute myelogenous leukaemia (aml) images using bright stretching technique |
publisher |
Universiti Malaysia Perlis (UniMAP) |
publishDate |
2012 |
url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/21623 |
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1643793415926710272 |