Wide-field multi-modal microscopic imaging using smartphone

Rabha, Diganta; Biswas, Sritam; Chamuah, Nabadweep; Mandal, Manab; Nath, Pabitra

doi:10.1016/j.optlaseng.2020.106343

Cited by 17 publications

(7 citation statements)

References 37 publications

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“…Various techniques have been employed to address this issue. Many papers have been published on bio-sensing for SARS-CoV-2, which uses direct immunoassays for amplification-free DNA or RNA biosensing (Pinheiro et al 2021 (Mu et al 2019), homemade smartphone using total internal reflection microscopy (Varra et al 2020), and multi-modal smartphone (bright-field, oblique illumination dark-field, and total internal reflection dark-field) on a single platform (Rabha et al 2021). An optical sensor device connecting through the 5 G network allows the Internet of Things (IoT) to identify single nucleic acids SARS-CoV 2 (Guo et al 2021).…”

Section: Covid-19 Diseases Monitoring Systemmentioning

confidence: 99%

Photonics enabled intelligence system to identify SARS-CoV 2 mutations

Taha

Al-Jubouri

Mashhadany

et al. 2022

Appl Microbiol Biotechnol

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The COVID-19, MERS-CoV, and SARS-CoV are hazardous epidemics that have resulted in many deaths which caused a worldwide debate. Despite control efforts, SARS-CoV-2 continues to spread, and the fast spread of this highly infectious illness has posed a grave threat to global health. The effect of the SARS-CoV-2 mutation, on the other hand, has been characterized by worrying variations that modify viral characteristics in response to the changing resistance profile of the human population. The repeated transmission of virus mutation indicates that epidemics are likely to occur. Therefore, an early identification system of ongoing mutations of SARS-CoV-2 will provide essential insights for planning and avoiding future outbreaks. This article discussed the following highlights: First, comparing the omicron mutation with other variants; second, analysis and evaluation of the spread rate of the SARS-CoV 2 variations in the countries; third, identification of mutation areas in spike protein; and fourth, it discussed the photonics approaches enabled with artificial intelligence. Therefore, our goal is to identify the SARS-CoV 2 virus directly without the need for sample preparation or molecular amplification procedures. Furthermore, by connecting through the optical network, the COVID-19 test becomes a component of the Internet of healthcare things to improve precision, service efficiency, and flexibility and provide greater availability for the evaluation of the general population. Key points• A proposed framework of photonics based on AI for identifying and sorting SARS-CoV 2 mutations. • Comparative scatter rates Omicron variant and other SARS-CoV 2 variations per country.• Evaluating mutation areas in spike protein and AI enabled by photonic technologies for SARS-CoV 2 virus detection.

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Section: Covid-19 Diseases Monitoring Systemmentioning

confidence: 99%

Photonics enabled intelligence system to identify SARS-CoV 2 mutations

Taha

Al-Jubouri

Mashhadany

et al. 2022

Appl Microbiol Biotechnol

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“…Similar to bench-top dark-field microscopes, in Figure 10 , smartphone-based dark-field microscopes can also use ring illumination [ 83 , 84 , 85 ]. Instead of a dark-field condenser to achieve ring illumination, the outer ring of the LED array can be activated to provide ring illumination by using a programmable LED array.…”

Section: Smart-phone Microscopymentioning

confidence: 99%

“… Smartphone-based dark-field microscopy based on ( a ) external angular illumination [ 84 ], and ( b ) a dark-field condenser [ 83 ]. …”

Section: Figurementioning

confidence: 99%

Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis

Bian

Xing

Jiao

et al. 2022

Cells

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In bio-medical mobile workstations, e.g., the prevention of epidemic viruses/bacteria, outdoor field medical treatment and bio-chemical pollution monitoring, the conventional bench-top microscopic imaging equipment is limited. The comprehensive multi-mode (bright/dark field imaging, fluorescence excitation imaging, polarized light imaging, and differential interference microscopy imaging, etc.) biomedical microscopy imaging systems are generally large in size and expensive. They also require professional operation, which means high labor-cost, money-cost and time-cost. These characteristics prevent them from being applied in bio-medical mobile workstations. The bio-medical mobile workstations need microscopy systems which are inexpensive and able to handle fast, timely and large-scale deployment. The development of lightweight, low-cost and portable microscopic imaging devices can meet these demands. Presently, for the increasing needs of point-of-care-test and tele-diagnosis, high-performance computational portable microscopes are widely developed. Bluetooth modules, WLAN modules and 3G/4G/5G modules generally feature very small sizes and low prices. And industrial imaging lens, microscopy objective lens, and CMOS/CCD photoelectric image sensors are also available in small sizes and at low prices. Here we review and discuss these typical computational, portable and low-cost microscopes by refined specifications and schematics, from the aspect of optics, electronic, algorithms principle and typical bio-medical applications.

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“…16 Several low-cost, portable microscopic imaging techniques have been reported using smartphones for clinical diagnosis and other monitoring applications such as cell sorting and counting. [17][18][19][20][21][22][23] As an illustration, researchers have demonstrated BF, fluorescence and other microscopic modalities on smartphones for the imaging and detection of water-borne parasites such as Giardia lamblia, human blood cells for the diagnosis of malaria and sickle cell anemia, tuberculosis diagnosis, detection of soil-transmitted helminths in stool samples, etc. 17,24-28 Smartphone microscopes, even with unity magnification, have proven their usability for imaging biological specimens due to the low pixel pitch (<1.6 µm) of the CMOS imaging sensor of the phone.…”

Section: Introductionmentioning

confidence: 99%