On-chip imaging of Schistosoma haematobium eggs in urine for diagnosis by computer vision.

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dc.contributor.authorLinder, Ewert
dc.contributor.authorGrote, Anne
dc.contributor.authorVarjo, Sami
dc.contributor.authorLinder, Nina
dc.contributor.authorLebbad, Marianne
dc.contributor.authorLundin, Mikael
dc.contributor.authorDiwan, Vinod
dc.contributor.authorHannuksela, Jari
dc.contributor.authorLundin, Johan
dc.date.accessioned2020-02-06T18:36:46Z
dc.date.available2020-02-06T18:36:46Z
dc.date.issued2013-12-16
dc.description.abstractBACKGROUND Microscopy being relatively easy to perform at low cost is the universal diagnostic method for detection of most globally important parasitic infections As quality control is hard to maintain misdiagnosis is common which affects both estimates of parasite burdens and patient care Novel techniques for high resolution imaging and image transfer over data networks may offer solutions to these problems through provision of education quality assurance and diagnostics Imaging can be done directly on image sensor chips a technique possible to exploit commercially for the development of inexpensive mini microscopes Images can be transferred for analysis both visually and by computer vision both at point of care and at remote locations METHODS PRINCIPAL FINDINGS Here we describe imaging of helminth eggs using mini microscopes constructed from webcams and mobile phone cameras The results show that an inexpensive webcam stripped off its optics to allow direct application of the test sample on the exposed surface of the sensor yields images of Schistosoma haematobium eggs which can be identified visually Using a highly specific image pattern recognition algorithm 4 out of 5 eggs observed visually could be identified CONCLUSIONS SIGNIFICANCE As proof of concept we show that an inexpensive imaging device such as a webcam may be easily modified into a microscope for the detection of helminth eggs based on on chip imaging Furthermore algorithms for helminth egg detection by machine vision can be generated for automated diagnostics The results can be exploited for constructing simple imaging devices for low cost diagnostics of urogenital schistosomiasis and other neglected tropical infectious diseases
dc.identifier.urihttp://dx.doi.org/10.1371/journal.pntd.0002547
dc.identifier.urihttps://lib.digitalsquare.io/xmlui/handle/123456789/6653
dc.relation.uriPLoS neglected tropical diseases
dc.subjectAt risk for a particular disease or infection
dc.subjectFacility-based health worker
dc.subjectAccess to information or data
dc.subjectQuality/unreliability of data
dc.subjectPrototype
dc.subjectUsability
dc.subjectExperimental
dc.subjectParastic Infections
dc.subjectDisease diagnosis / Point-of-care diagnostics
dc.subjectData collection and reporting
dc.subjectImage
dc.subjectCamera
dc.titleOn-chip imaging of Schistosoma haematobium eggs in urine for diagnosis by computer vision.en
dcterms.abstractBACKGROUND Microscopy being relatively easy to perform at low cost is the universal diagnostic method for detection of most globally important parasitic infections As quality control is hard to maintain misdiagnosis is common which affects both estimates of parasite burdens and patient care Novel techniques for high resolution imaging and image transfer over data networks may offer solutions to these problems through provision of education quality assurance and diagnostics Imaging can be done directly on image sensor chips a technique possible to exploit commercially for the development of inexpensive mini microscopes Images can be transferred for analysis both visually and by computer vision both at point of care and at remote locations METHODS PRINCIPAL FINDINGS Here we describe imaging of helminth eggs using mini microscopes constructed from webcams and mobile phone cameras The results show that an inexpensive webcam stripped off its optics to allow direct application of the test sample on the exposed surface of the sensor yields images of Schistosoma haematobium eggs which can be identified visually Using a highly specific image pattern recognition algorithm 4 out of 5 eggs observed visually could be identified CONCLUSIONS SIGNIFICANCE As proof of concept we show that an inexpensive imaging device such as a webcam may be easily modified into a microscope for the detection of helminth eggs based on on chip imaging Furthermore algorithms for helminth egg detection by machine vision can be generated for automated diagnostics The results can be exploited for constructing simple imaging devices for low cost diagnostics of urogenital schistosomiasis and other neglected tropical infectious diseases
dcterms.contributorLinder, Ewert
dcterms.contributorGrote, Anne
dcterms.contributorVarjo, Sami
dcterms.contributorLinder, Nina
dcterms.contributorLebbad, Marianne
dcterms.contributorLundin, Mikael
dcterms.contributorDiwan, Vinod
dcterms.contributorHannuksela, Jari
dcterms.contributorLundin, Johan
dcterms.identifierhttp://dx.doi.org/10.1371/journal.pntd.0002547
dcterms.relationPLoS neglected tropical diseases
dcterms.subjectAt risk for a particular disease or infection
dcterms.subjectFacility-based health worker
dcterms.subjectAccess to information or data
dcterms.subjectQuality/unreliability of data
dcterms.subjectPrototype
dcterms.subjectUsability
dcterms.subjectExperimental
dcterms.subjectParastic Infections
dcterms.subjectDisease diagnosis / Point-of-care diagnostics
dcterms.subjectData collection and reporting
dcterms.subjectImage
dcterms.subjectCamera
dcterms.titleOn-chip imaging of Schistosoma haematobium eggs in urine for diagnosis by computer vision.en
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