A review on automated diagnosis of malaria parasite in microscopic blood smears images

Author:

Jan Zahoor,Khan Arshad,Sajjad Muhammad,Muhammad Khan,Rho Seungmin,Mehmood Irfan

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference87 articles.

1. Abdul-Nasir AS, Mashor MY, Mohamed Z (2012) Modified global and modified linear contrast stretching algorithms: new colour contrast enhancement techniques for microscopic analysis of malaria slide images. Computational and Mathematical Methods in Medicine, vol. 2012. Article ID 637360, p 16

2. Aimi Salihah A-N, Yusoff M, Zeehaida M (2013) Colour image segmentation approach for detection of malaria parasites using various colour models and k-means clustering. Wseas Transactions on Biology and Biomedicine, vol. 10

3. Malaria Site – History, Pathogenesis, Clinical Features, Diagnosis, Treatment, Complications and Control of Malaria. (n.d.). Retrieved September, 2015, from: http://www.malariasite.com

4. Anggraini D et al (2011) Automated status identification of microscopic images obtained from malaria thin blood smears. In Electrical Engineering and Informatics (ICEEI), 2011 International conference on. 17:347–352 IEEE

5. Arco J et al (2015) Digital image analysis for automatic enumeration of malaria parasites using morphological operations. Expert Systems with Applications, 42(6):3041–3047

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