Smart-phone phase contrast microscope with a singlet lens and deep learning

Bian, Yinxu; Jiang, Yannan; Huang, Yuran; Yang, Xiaofei; Deng, Wei; Shen, Hua; Shen, Renbing; Kuang, Cuifang

doi:10.1016/j.optlastec.2020.106900

Cited by 16 publications

(10 citation statements)

References 37 publications

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“…Computational algorithms empower recent smartphone microscopes with the additional target recognition ability. Machine vision and deep learning have been incorporated in microscope image analysis, as exemplified in [73], [74]. Spatial resolutions of computational smartphone-based microscopes are also enhanced.…”

Section: Smartphone-based Microscopesmentioning

confidence: 99%

Smart scientific instruments based on smartphones: a brief review

Sirisathitkul

Sirisathitkul²

2023

IJECE

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<span>Smartphone has gone beyond a communication hub to be a measurement device itself, thanks to various built-in sensors. This article reviewed achievements in transforming ubiquitous smartphones into cost-effective scientific instruments for educational laboratories, environmental studies, point-of-care diagnostics, home-based health monitoring, and rehabilitation. Magnetic fields were precisely measured by built-in magnetometers, leading to demonstrations for engineering and medical applications. The smartphone-based joint-angle measurement was a viable alternative to traditional goniometers. Characterizations of optical signals captured by cameras led to portable spectrophotometers and colorimeters for both educational and practical uses. Interestingly, smartphones became a platform for high-resolution microscopes and fluorescence microscopes were developed with add-on components. These smart instruments become even more attractive options in the pandemic period with limited facility and laboratory access.</span>

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Section: Smartphone-based Microscopesmentioning

confidence: 99%

Smart scientific instruments based on smartphones: a brief review

Sirisathitkul

Sirisathitkul²

2023

IJECE

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“…[69] A smartphone-based portable singlet PCM was presented to acquire a phase contrast image (Figure 4B,C). [70] This device consists of an illumination part including a LED, a diffuser, a circular stop, and an imaging part including a customized aspheric singlet lens and a smartphone. The axial stage that controls the sample position is also assembled in the 3D-printed demo setup.…”

Section: Phase-contrast Microscopic Systemsmentioning

confidence: 99%

Portable, Automated and Deep‐Learning‐Enabled Microscopy for Smartphone‐Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review

Kim

Lee

2022

Small Methods

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Globally new pandemic diseases induce urgent demands for portable diagnostic systems to prevent and control infectious diseases. Smartphone‐based portable diagnostic devices are significantly efficient tools to user‐friendly connect personalized health conditions and collect valuable optical information for rapid diagnosis and biomedical research through at‐home screening. Deep learning algorithms for portable microscopes also help to enhance diagnostic accuracy by reducing the imaging resolution gap between benchtop and portable microscopes. This review highlighted recent progress and continued efforts in a smartphone‐tethered optical platform through portable, automated, and deep‐learning‐enabled microscopy for personalized diagnostics and remote monitoring. In detail, the optical platforms through smartphone‐based microscopes and lens‐free holographic microscopy are introduced, and deep learning‐based portable microscopic imaging is explained to improve the image resolution and accuracy of diagnostics. The challenges and prospects of portable optical systems with microfluidic channels and a compact microscope to screen COVID‐19 in the current pandemic are also discussed. It has been believed that this review offers a novel guide for rapid diagnosis, biomedical imaging, and digital healthcare with low cost and portability.

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“…Due to the higher cost of the associated optical hardware and the complexity of the system, their applications are limited. Now, computational, low-cost and portable microscopes based on smartphone platforms make label-free phase contrast techniques useful and possible in the fields of on-site testing and remote medical diagnosis [ 79 , 80 , 81 , 82 ]. To improve the quality of phase contrast images collected by smart-phone microscopes, deep learning networks can also transfer the style of directly collected images.…”

Section: Smart-phone Microscopymentioning

confidence: 99%

“…Shen et al propose a deep learning singlet microscope with imaging performance competitive with research-level commercial microscopes [ 81 , 105 , 106 , 107 ]. It has a total size of about 10 cm × 10 cm × 20 cm and weighs only 400 g. The resolution is up to 1.38 μm and a large FOV (diagonal 5 mm) is achieved.…”

Section: Singlet Microscopymentioning

confidence: 99%

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

Bian

Xing

Jiao

et al. 2022

Cells

Self Cite

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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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Smart-phone phase contrast microscope with a singlet lens and deep learning

Cited by 16 publications

References 37 publications

Smart scientific instruments based on smartphones: a brief review

Smart scientific instruments based on smartphones: a brief review

Portable, Automated and Deep‐Learning‐Enabled Microscopy for Smartphone‐Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review

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

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