Literature DB >> 22255740

Ontology-based malaria parasite stage and species identification from peripheral blood smear images.

Vishnu V Makkapati1, Raghuveer M Rao.   

Abstract

The diagnosis and treatment of malaria infection requires detecting the presence of the malaria parasite in the patient as well as identification of the parasite species. We present an image processing-based approach to detect parasites in microscope images of a blood smear and an ontology-based classification of the stage of the parasite for identifying the species of infection. This approach is patterned after the diagnosis approach adopted by a pathologist for visual examination, and hence, is expected to deliver similar results. We formulate several rules based on the morphology of the basic components of a parasite, namely, chromatin dot(s) and cytoplasm, to identify the parasite stage and species. Numerical results are presented for data taken from various patients. A sensitivity of 88% and a specificity of 95% is reported by evaluation of the scheme on 55 images.

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Year:  2011        PMID: 22255740     DOI: 10.1109/IEMBS.2011.6091516

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  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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