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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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Bibliographic Details
Main Authors: F.H.A., Jabar,, W., Ismail,, R.A., Salam,, R, Hassan,
Format: Conference Paper
Language:en_US
Published: IEEE Computer Society 2015
Subjects:
Acute leukemia cells
Clustering
Image segmentation
K-means
Mean shift
Online Access:http://ddms.usim.edu.my/handle/123456789/9204
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Summary: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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