Mobile Phone Based Clinical Microscopy for Global Health Applications
By David N. Breslauer, R. Maamari, N. Switz, W. Lam, D. Fletcher. PLoS ONE, 2009
707 citations recorded by the source corpus.
Light microscopy provides a simple, cost-effective, and vital method for the diagnosis and screening of hematologic and infectious diseases. In many regions of the world, however, the required equipment is either unavailable or insufficiently portable, and operators may not possess adequate training to make full use of the images obtained. Counterintuitively, these same regions are often well served by mobile phone networks, suggesting the possibility of leveraging portable, camera-enabled mobile phones for diagnostic imaging and telemedicine. Toward this end we have built a mobile phone-mounted light microscope and demonstrated its potential for clinical use by imaging P. falciparum-infected and sickle red blood cells in brightfield and M. tuberculosis-infected sputum samples in fluorescence with LED excitation. In all cases resolution exceeded that necessary to detect blood cell and microorganism morphology, and with the tuberculosis samples we took further advantage of the digitized images to demonstrate automated bacillus counting via image analysis software. We expect such a telemedicine system for global healthcare via mobile phone – offering inexpensive brightfield and fluorescence microscopy integrated with automated image analysis – to provide an important tool for disease diagnosis and screening, particularly in the developing world and rural areas where laboratory facilities are scarce but mobile phone infrastructure is extensive.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/e6ac378ce1ad7a777efc36396b7bb9d59ed0da87
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In Computer Vision and Pattern Recognition
Citations in the corpus
- Amplification-free detection of SARS-CoV-2 with CRISPR-Cas13a and mobile phone microscopy (2020, neutral): “The high sensitivity of mobile phone cameras, together with their connectivity, GPS, and data-processing capabilities, have made them attractive tools for point-of-care disease diagnosis in lowresource regions (Breslauer et al., 2009; D’Ambrosio et al., 2015; Kamgno et al., 2017; Wood et al., 2019).”
- Smartphone based bacterial detection using biofunctionalized fluorescent nanoparticles (2014, background): “Smartphone cameras have been previously shown to be a portable microscope for monitoring pathogens, inexpensive spectrophotometer for educational purpose [18, 19].”
- Image analysis and machine learning for detecting malaria (2018, background): “[15] Breslauer DN, Maamari RN, Switz NA, Lam WA, Fletcher DA.”