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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15708
Title: Automatic classification of leukocytes using morphological features and Naïve Bayes classifier
Authors: Gautam A.
Singh P.
Raman B.
Bhadauria H.
Published in: Proceedings of IEEE Region 10 Annual International Conference, Proceedings/TENCON
Abstract: In human body, different types of diseases can be found while examining blood samples. In this paper, the main aim is to detect leukocytes from human blood. These leukocytes protect the body from infectious diseases. If there is any type of disturbances in the blood count, then it may signify the presence of some cancer. Due to this reason, earlier many hematological experts examined blood samples by using medical instruments such as flow cytometer, for determining what type of disease is present in the human body. Since, the manual segmentation remains a very soporific, tiresome and error prone job, experts preferred to use automatic systems that results in accurate segmentation of leukocytes, which is needed for their classification. In this paper, the simple thresholding technique is used for segmentation of leukocytes by using Otsu thresholding. After segmentation, mathematical morphing is used to remove all components those do not look like leukocytes. Further, only the nucleus region was considered for feature extraction. Thereafter, Naïve Bayes classification technique is used for classification of leukocytes. The results obtained are better than other state of art algorithms, the classification accuracy on the training dataset of only 20 images and test image dataset of 68 images is about 80.88%, in an average time of 22 s per image. © 2016 IEEE.
Citation: Proceedings of IEEE Region 10 Annual International Conference, Proceedings/TENCON, (2017), 1023- 1027
URI: https://doi.org/10.1109/TENCON.2016.7848161
http://repository.iitr.ac.in/handle/123456789/15708
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: leukocytes or white blood cells (WBC)
mathematical morphing
Naïve Bays classifier
segmentation
ISBN: 9781509025961
ISSN: 21593442
Author Scopus IDs: 57196216030
57212591690
23135470700
37088115100
Author Affiliations: Gautam, A., Computer Science and Engineering, Indian Institute of Technology, Roorkee, India
Singh, P., Computer Science and Engineering, Indian Institute of Technology, Roorkee, India
Raman, B., Computer Science and Engineering, Indian Institute of Technology, Roorkee, India
Bhadauria, H., Computer Science and Engineering, G.B. Pant Engineering College, Pauri Gahwal, India
Appears in Collections:Conference Publications [CS]

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