ArticlePLoS neglected tropical diseases2013
On-chip imaging of Schistosoma haematobium eggs in urine for diagnosis by computer vision.
Article in PLoS neglected tropical diseases, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 44 citations in OpenAlex.
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- Diagnosis of Human Trematode Infections.Advances in experimental medicine and biology · 2024Review
- Performance evaluation of the AiDx multi-diagnostic automated microscope for the detection of schistosomiasis in Abuja, Nigeria.Scientific reports · 2023Article
- A review on innovative optical devices for the diagnosis of human soil-transmitted helminthiasis and schistosomiasis: from research and development to commercialization.Parasitology · 2023Review
- High Sensitivity of Mobile Phone Microscopy Screening for Schistosoma haematobium in Azaguié, Côte d'Ivoire.The American journal of tropical medicine and hygiene · 2023Article
- Performance Evaluation of the Schistoscope 5.0 for (Semi-)automated Digital Detection and Quantification of Schistosoma haematobium Eggs in Urine: A Field-based Study in Nigeria.The American journal of tropical medicine and hygiene · 2022Article
- Aspects of Point-of-Care Diagnostics for Personalized Health Wellness.International journal of nanomedicine · 2021Review
- Rapid Yeast Cell Viability Analysis by Using a Portable Microscope Based on the Fiber Optic Array and Simple Image Processing.Sensors (Basel, Switzerland) · 2020Article
- International Society of Nephrology's 0by25 initiative (zero preventable deaths from acute kidney injury by 2025): focus on diagnosis of acute kidney injury in low-income countries.Clinical kidney journal · 2018Article
- "Smart Diagnosis" of Parasitic Diseases by Use of Smartphones.Journal of clinical microbiology · 2018Review
- Mobile-phone and handheld microscopy for neglected tropical diseases.PLoS neglected tropical diseases · 2017Article
- Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium.Global health action · 2017Article
- Evaluation of a Mobile Phone-Based Microscope for Screening ofThe American journal of tropical medicine and hygiene · 2017Article
- Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle.Diagnostics (Basel, Switzerland) · 2016Article
- Accuracy of Mobile Phone and Handheld Light Microscopy for the Diagnosis of Schistosomiasis and Intestinal Protozoa Infections in Côte d'Ivoire.PLoS neglected tropical diseases · 2016Article
- Review of Telemicrobiology.Archives of pathology & laboratory medicine · 2016Review
- Smartphone Microscopy of Parasite Eggs Accumulated into a Single Field of View.The American journal of tropical medicine and hygiene · 2016Article
- Disposable optics for microscopy diagnostics.Scientific reports · 2015Article
- Advances in the Diagnosis of Human Schistosomiasis.Clinical microbiology reviews · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicroscopy, 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
findingsHere 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.