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A Novel Approach to Detect Chronic Leukemia using Shape based Feature Extraction and Identification with Digital Image Processing

Himali Vaghela, Hardik Modi, Manoj Pandya, M. B. Potdar. Published in Information Science

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Himali Vaghela, Hardik Modi, Manoj Pandya, M. B. Potdar
10.5120/ijais2016451607
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  1. Himali Vaghela, Hardik Modi, Manoj Pandya and M B Potdar. A Novel Approach to Detect Chronic Leukemia using Shape based Feature Extraction and Identification with Digital Image Processing. International Journal of Applied Information Systems 11(5):9-16, October 2016. URL, DOI BibTeX

    @article{10.5120/ijais2016451607,
    	author = "Himali Vaghela and Hardik Modi and Manoj Pandya and M. B. Potdar",
    	title = "A Novel Approach to Detect Chronic Leukemia using Shape based Feature Extraction and Identification with Digital Image Processing",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "October 2016",
    	volume = 11,
    	number = 5,
    	month = "Oct",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "9-16",
    	numpages = 8,
    	url = "http://www.ijais.org/archives/volume11/number5/941-2016451607",
    	doi = "10.5120/ijais2016451607",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

In this paper, some shape based features like area, perimeter, roundness, standard deviation etc. are used to recognize different types of white blood cells like monocyte, lymphocytes, eosinophil, basophil, neutrophils etc. Using image processing techniques, result can be obtained within 3-4 minute. To perform shape base features operation, contrast of RGB image has to be increased for better detection of white cells. After recognition of each and every cell, classification is performed to detect either it is CML (Chronic Myelogenous Leukemia) or CLL (chronic Lymphocytic leukemia). This algorithm is performed on 30 images. Out of 30, it is successful on 28 images. So it gives accuracy of 93.33%.

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Keywords

Chronic leukemia detection, shape based features extraction and identification, image classification, Medical Image Processing