Computer vision for microscopy diagnosis of malaria
Abstract This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of...
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ftdoajarticles:oai:doaj.org/article:62a4118ef0db402b9ad89ed562ae22c1 2023-05-15T14:59:43+02:00 Computer vision for microscopy diagnosis of malaria Dempster Andrew G Tek F Boray Kale Izzet 2009-07-01T00:00:00Z https://doi.org/10.1186/1475-2875-8-153 https://doaj.org/article/62a4118ef0db402b9ad89ed562ae22c1 EN eng BMC http://www.malariajournal.com/content/8/1/153 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-8-153 1475-2875 https://doaj.org/article/62a4118ef0db402b9ad89ed562ae22c1 Malaria Journal, Vol 8, Iss 1, p 153 (2009) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2009 ftdoajarticles https://doi.org/10.1186/1475-2875-8-153 2022-12-31T13:40:19Z Abstract This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 8 1 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Dempster Andrew G Tek F Boray Kale Izzet Computer vision for microscopy diagnosis of malaria |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided. |
format |
Article in Journal/Newspaper |
author |
Dempster Andrew G Tek F Boray Kale Izzet |
author_facet |
Dempster Andrew G Tek F Boray Kale Izzet |
author_sort |
Dempster Andrew G |
title |
Computer vision for microscopy diagnosis of malaria |
title_short |
Computer vision for microscopy diagnosis of malaria |
title_full |
Computer vision for microscopy diagnosis of malaria |
title_fullStr |
Computer vision for microscopy diagnosis of malaria |
title_full_unstemmed |
Computer vision for microscopy diagnosis of malaria |
title_sort |
computer vision for microscopy diagnosis of malaria |
publisher |
BMC |
publishDate |
2009 |
url |
https://doi.org/10.1186/1475-2875-8-153 https://doaj.org/article/62a4118ef0db402b9ad89ed562ae22c1 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 8, Iss 1, p 153 (2009) |
op_relation |
http://www.malariajournal.com/content/8/1/153 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-8-153 1475-2875 https://doaj.org/article/62a4118ef0db402b9ad89ed562ae22c1 |
op_doi |
https://doi.org/10.1186/1475-2875-8-153 |
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Malaria Journal |
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8 |
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1 |
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1766331825961041920 |