Literature DB >> 22906011

Combining kriging, multispectral and multimodal microscopy to resolve malaria-infected erythrocyte contents.

S Dabo-Niang1, J T Zoueu.   

Abstract

In this communication, we demonstrate how kriging, combine with multispectral and multimodal microscopy can enhance the resolution of malaria-infected images and provide more details on their composition, for analysis and diagnosis. The results of this interpolation applied to the two principal components of multispectral and multimodal images illustrate that the examination of the content of Plasmodium falciparum infected human erythrocyte is improved.
© 2012 The Authors Journal of Microscopy © 2012 Royal Microscopical Society.

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Year:  2012        PMID: 22906011     DOI: 10.1111/j.1365-2818.2012.03637.x

Source DB:  PubMed          Journal:  J Microsc        ISSN: 0022-2720            Impact factor:   1.758


  2 in total

Review 1.  Image analysis and machine learning for detecting malaria.

Authors:  Mahdieh Poostchi; Kamolrat Silamut; Richard J Maude; Stefan Jaeger; George Thoma
Journal:  Transl Res       Date:  2018-01-12       Impact factor: 7.012

Review 2.  Computational Methods for Automated Analysis of Malaria Parasite Using Blood Smear Images: Recent Advances.

Authors:  Shankar Shambhu; Deepika Koundal; Prasenjit Das; Vinh Truong Hoang; Kiet Tran-Trung; Hamza Turabieh
Journal:  Comput Intell Neurosci       Date:  2022-04-11
  2 in total

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