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Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging
In many malaria‐endemic regions, current detection tools are inadequate in diagnostic accuracy and accessibility. To meet the need for direct, phenotypic, and automated malaria parasite detection in field settings, a portable platform to process, image, and analyze whole blood to detect Plasmodium f...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534981/ https://www.ncbi.nlm.nih.gov/pubmed/35957519 http://dx.doi.org/10.1002/advs.202105396 |
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author | Deshmukh, Shreya S. Byaruhanga, Oswald Tumwebaze, Patrick Akin, Demir Greenhouse, Bryan Egan, Elizabeth S. Demirci, Utkan |
author_facet | Deshmukh, Shreya S. Byaruhanga, Oswald Tumwebaze, Patrick Akin, Demir Greenhouse, Bryan Egan, Elizabeth S. Demirci, Utkan |
author_sort | Deshmukh, Shreya S. |
collection | PubMed |
description | In many malaria‐endemic regions, current detection tools are inadequate in diagnostic accuracy and accessibility. To meet the need for direct, phenotypic, and automated malaria parasite detection in field settings, a portable platform to process, image, and analyze whole blood to detect Plasmodium falciparum parasites, is developed. The liberated parasites from lysed red blood cells suspended in a magnetic field are accurately detected using this cellphone‐interfaced, battery‐operated imaging platform. A validation study is conducted at Ugandan clinics, processing 45 malaria‐negative and 36 malaria‐positive clinical samples without external infrastructure. Texture and morphology features are extracted from the sample images, and a random forest classifier is trained to assess infection status, achieving 100% sensitivity and 91% specificity against gold‐standard measurements (microscopy and polymerase chain reaction), and limit of detection of 31 parasites per µL. This rapid and user‐friendly platform enables portable parasite detection and can support malaria diagnostics, surveillance, and research in resource‐constrained environments. |
format | Online Article Text |
id | pubmed-9534981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95349812022-10-11 Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging Deshmukh, Shreya S. Byaruhanga, Oswald Tumwebaze, Patrick Akin, Demir Greenhouse, Bryan Egan, Elizabeth S. Demirci, Utkan Adv Sci (Weinh) Research Articles In many malaria‐endemic regions, current detection tools are inadequate in diagnostic accuracy and accessibility. To meet the need for direct, phenotypic, and automated malaria parasite detection in field settings, a portable platform to process, image, and analyze whole blood to detect Plasmodium falciparum parasites, is developed. The liberated parasites from lysed red blood cells suspended in a magnetic field are accurately detected using this cellphone‐interfaced, battery‐operated imaging platform. A validation study is conducted at Ugandan clinics, processing 45 malaria‐negative and 36 malaria‐positive clinical samples without external infrastructure. Texture and morphology features are extracted from the sample images, and a random forest classifier is trained to assess infection status, achieving 100% sensitivity and 91% specificity against gold‐standard measurements (microscopy and polymerase chain reaction), and limit of detection of 31 parasites per µL. This rapid and user‐friendly platform enables portable parasite detection and can support malaria diagnostics, surveillance, and research in resource‐constrained environments. John Wiley and Sons Inc. 2022-08-11 /pmc/articles/PMC9534981/ /pubmed/35957519 http://dx.doi.org/10.1002/advs.202105396 Text en © 2022 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Deshmukh, Shreya S. Byaruhanga, Oswald Tumwebaze, Patrick Akin, Demir Greenhouse, Bryan Egan, Elizabeth S. Demirci, Utkan Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging |
title | Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging |
title_full | Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging |
title_fullStr | Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging |
title_full_unstemmed | Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging |
title_short | Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging |
title_sort | automated recognition of plasmodium falciparum parasites from portable blood levitation imaging |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534981/ https://www.ncbi.nlm.nih.gov/pubmed/35957519 http://dx.doi.org/10.1002/advs.202105396 |
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