Automatic leukocyte nucleus segmentation by intuitionistic fuzzy divergence based thresholding

Jati, Arindam and Singha, Garima and Mukherjee, Rashmi and Ghoshb, Madhumala and Konar, Amit and Chakraborty, Chandan and Nagar, Atulya K. (2014) Automatic leukocyte nucleus segmentation by intuitionistic fuzzy divergence based thresholding. Micron, 58. pp. 55-65. ISSN 0968-4328

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Abstract

The paper proposes a robust approach to automatic segmentation of leukocyte‟s nucleus from microscopic blood smear images under normal as well as noisy environment by employing a new exponential intuitionistic fuzzy divergence based thresholding technique. The algorithm minimizes the divergence between the actual image and the ideally thresholded image to search for the final threshold. A new divergence formula based on exponential intuitionistic fuzzy entropy has been proposed. Further, to increase its noise handling capacity, a neighborhood-based membership function for the image pixels has been designed. The proposed scheme has been applied on 110 normal and 54 leukemia (chronic myelogenous leukemia) affected blood samples. The nucleus segmentation results have been validated by three expert haematologists. The algorithm achieves an average segmentation accuracy of 98.52% in noise-free environment. It beats the competitor algorithms in terms of several other metrics. The proposed scheme with neighborhood based membership function outperforms the competitor algorithms in terms of segmentation accuracy under noisy environment. It achieves 93.90% and 94.93% accuracies for Speckle and Gaussian noises respectively. The average area under the ROC curves comes out to be 0.9514 in noisy conditions, which proves the robustness of the proposed algorithm.

Item Type: Article
Additional Information and Comments: “NOTICE: this is the author’s version of a work that was accepted for publication in Micron. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Micron, vol 58 March 2014, p.55-65. DOI 10.1016/j.micron.2013.12.001
Keywords: Leukocyte nucleus segmentation, Intuitionistic fuzzy set (IFS), Intuitionistic fuzzy divergence (IFD), membership function, non-membership function, intuitionistic fuzzy generator (IFG)
Faculty / Department: Faculty of Science > Mathematics and Computer Science
Depositing User: Philippe Chassy
Date Deposited: 19 Jan 2015 17:34
Last Modified: 19 Jan 2015 17:34
URI: http://hira.hope.ac.uk/id/eprint/413

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