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Title: Unsupervised colour segmentation of white blood cell for acute leukaemia images
Authors: A. S., Abdul Nasir
Mohd Yusoff, Mashor, Prof. Dr.
H., Rosline
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Keywords: Acute leukemia;Colour segmentation;HSI colour space;K-means clustering;Linear contrast
Issue Date: 2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p. 142-145
Series/Report no.: Proceedings of the International Conference on Imaging Systems and Techniques (IST 2011)
Abstract: Colour image segmentation has becoming more popular for computer vision due to its important process in most medical analysis tasks. One of the main tasks is the segmentation of white blood cell (WBC) where the WBC composition reveals important diagnostic information of a patient. In this paper, the combination between linear contrast technique and colour segmentation based on HSI (Hue, Saturation, Intensity) colour space were used in order to obtain a fully segmented abnormal WBC and nucleus of acute leukaemia images. The unsupervised segmentation technique namely k-means clustering algorithm is used to ease the segmentation process. By implementing the proposed segmentation technique, the fully segmented WBC which consists of cytoplasm and nucleus regions can be achieved by using the combination of linear contrast technique and segmentation based on H component image. Meanwhile, the fully segmented nucleus can be obtained by applying the segmentation based on S component image. The combinations between linear contrast technique and segmentation based on HSI colour space have produced a better effect on improving the accuracy of WBC segmentation with segmentation accuracies of 99.02% and 99.05% for segmented WBC and nucleus, respectively.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5962188&tag=1
ISBN: 978-1-6128-4896-9
Appears in Collections:Conference Papers
Mohd Yusoff Mashor, Prof. Dr.

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