Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images
Clustering is one of the most common automated image segmentation techniques used in many fields including machine learning, pattern recognition, image processing, and bioinformatics. Recently many scientists have performed tremendous research in helping the hematologists in the issue of segmenting...
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my.usim-92042017-03-16T02:49:53Z Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images F.H.A., Jabar, W., Ismail, R.A., Salam, R, Hassan, Acute leukemia cells Clustering Image segmentation K-means Mean shift Clustering is one of the most common automated image segmentation techniques used in many fields including machine learning, pattern recognition, image processing, and bioinformatics. Recently many scientists have performed tremendous research in helping the hematologists in the issue of segmenting the blood cells in the early of prognosis. This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. The integrated clustering techniques have produced comprehensive output images with minimal filtering process to remove the background scene. © 2013 IEEE. 2015-08-25T04:56:14Z 2015-08-25T04:56:14Z 2014 Conference Paper 9781-4799-2758-6 http://ddms.usim.edu.my/handle/123456789/9204 en_US IEEE Computer Society |
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Acute leukemia cells Clustering Image segmentation K-means Mean shift F.H.A., Jabar, W., Ismail, R.A., Salam, R, Hassan, Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
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Clustering is one of the most common automated image segmentation techniques used in many fields including machine learning, pattern recognition, image processing, and bioinformatics. Recently many scientists have performed tremendous research in helping the hematologists in the issue of segmenting the blood cells in the early of prognosis. This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. The integrated clustering techniques have produced comprehensive output images with minimal filtering process to remove the background scene. © 2013 IEEE. |
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Conference Paper |
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F.H.A., Jabar, W., Ismail, R.A., Salam, R, Hassan, |
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F.H.A., Jabar, W., Ismail, R.A., Salam, R, Hassan, |
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F.H.A., Jabar, |
title |
Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
title_short |
Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
title_full |
Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
title_fullStr |
Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
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image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images |
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IEEE Computer Society |
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2015 |
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http://ddms.usim.edu.my/handle/123456789/9204 |
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