On-Chip Imaging of Schistosoma haematobium Eggs in Urine for Diagnosis by Computer Vision

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/SignificanceAs 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.

Diagnosis of Schistosoma haematobium Infection with a Mobile Phone-Mounted Foldscope and a Reversed-Lens CellScope in Ghana

“…Other recent innovations may aid in the field diagnosis of S. haematobium infection as well, including a low-cost Millipore filtration device, 17 or on-chip imaging of ova, 18 both of which showed promise in early proof-of-concept studies. However, all will require vigorous field testing in clinical and public health settings before implementation.…”

Advances in the Diagnosis of Human Schistosomiasis

“…A novel approach for the direct detection of schistosome eggs is by computer-directed visual identification using minimicroscopes constructed from inexpensive imaging devices, such as mobile phones or Web cams, with samples placed directly on the image sensor (79). The image analysis can be done locally or using a distally located computer for the interpretation of results, and these methods widen the possibilities of using copro-microscopic diagnostics in resource-poor settings.…”

Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium

“…helminths or schistosomes) typically requires examination of significantly larger areas, especially with samples showing low levels of infection or when assessing infection rate. Benefits of digital microscopy compared to light microscopy include real-time data sharing for remote diagnosis and consultations to facilitate faster diagnosis [25,26], and the possibility of utilizing digital image analysis to aid in sample analysis [27]. …”