Machine learning approach of automatic identification and counting of blood cells-Reference-Cited by-同舟云学术

Machine learning approach of automatic identification and counting of blood cells

Published:2019-07-17 Issue:4 Volume:6 Page:103-108
ISSN:2053-3713
Container-title:Healthcare Technology Letters
language:en
Short-container-title:Healthcare Technology Letters

Author:

Alam Mohammad Mahmudul¹,Islam Mohammad Tariqul¹

Affiliation:

1. Department of EEE Bangladesh University of Engineering and Technology Dhaka Bangladesh

Publisher

Institution of Engineering and Technology (IET)

Subject

Health Information Management,Health Informatics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/htl.2018.5098

Reference20 articles.

1. Cruz D. Jennifer C. Valiente L.C. et al. : ‘Determination of blood components (WBCs RBCs and platelets) count in microscopic images using image processing and analysis’.Proc. Int. Conf. on Humanoid Nanotechnology Information Technology Communication and Control Environment and Management (HNICEM) December2017

2. Habibzadeh M. KrzyÅijak A. Fevens T.: ‘White blood cell differential counts using convolutional neural networks for low resolution images’.Proc. Int. Conf. on Artificial Intelligence and Soft Computing 2013 pp.263–274

3. Acharjee S. Chakrabartty S. Alam M.I. et al. : ‘A semiautomated approach using GUI for the detection of red blood cells’.Proc. Int. Conf. on Electrical Electronics and Optimization Techniques 2016 pp.525–529

4. Lou J. Zhou M. Li Q. et al. : ‘An automatic red blood cell counting method based on spectral images’.Proc. Int. Congress on Image and Signal Processing BioMedical Engineering and Informatics October2016 pp.1391–1396

5. Islam M.T. Aowal M.A. Minhaz A.T. et al. : ‘Abnormality detection and localization in chest X‐rays using deep convolutional neural networks’ arXiv preprint arXiv:1705.09850v3 2017

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