Towards ultra-low-cost smartphone microscopy (2312.11479v1)
Abstract: The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ~9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ~5 micron, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we use an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We use the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance.
- S. Banik, S. K. Melanthota, Arbaaz, J. M. Vaz, V. M. Kadambalithaya, I. Hussain, S. Dutta, and N. Mazumder, “Recent trends in smartphone-based detection for biomedical applications: a review,” \JournalTitleAnalytical and Bioanalytical Chemistry 413, 2389–2406 (2021).
- I. Hussain and A. K. Bowden, “Smartphone-based optical spectroscopic platforms for biomedical applications: a review,” \JournalTitleBiomedical optics express 12, 1974–1998 (2021).
- B. Hunt, A. J. Ruiz, and B. W. Pogue, “Smartphone-based imaging systems for medical applications: a critical review,” \JournalTitleJournal of Biomedical Optics 26, 040902–040902 (2021).
- S. Ravindran, “Smartphone science: apps test and track infectious diseases.” \JournalTitleNature 593, 302–303 (2021).
- P. Fozouni, S. Son, M. D. de León Derby, G. J. Knott, C. N. Gray, M. V. D’Ambrosio, C. Zhao, N. A. Switz, G. R. Kumar, S. I. Stephens et al., “Amplification-free detection of sars-cov-2 with crispr-cas13a and mobile phone microscopy,” \JournalTitleCell 184, 323–333 (2021).
- A. Ganguli, A. Mostafa, J. Berger, M. Y. Aydin, F. Sun, S. A. S. de Ramirez, E. Valera, B. T. Cunningham, W. P. King, and R. Bashir, “Rapid isothermal amplification and portable detection system for sars-cov-2,” \JournalTitleProceedings of the National Academy of Sciences 117, 22727–22735 (2020).
- L. Jin, Y. Tang, Y. Wu, J. B. Coole, M. T. Tan, X. Zhao, H. Badaoui, J. T. Robinson, M. D. Williams, A. M. Gillenwater et al., “Deep learning extended depth-of-field microscope for fast and slide-free histology,” \JournalTitleProceedings of the National Academy of Sciences 117, 33051–33060 (2020).
- D. Sun and T. Y. Hu, “A low cost mobile phone dark-field microscope for nanoparticle-based quantitative studies,” \JournalTitleBiosensors and Bioelectronics 99, 513–518 (2018).
- S. Knowlton, A. Joshi, P. Syrrist, A. F. Coskun, and S. Tasoglu, “3d-printed smartphone-based point of care tool for fluorescence-and magnetophoresis-based cytometry,” \JournalTitleLab on a Chip 17, 2839–2851 (2017).
- A. Orth, E. Wilson, J. Thompson, and B. Gibson, “A dual-mode mobile phone microscope using the onboard camera flash and ambient light,” \JournalTitleScientific reports 8, 3298 (2018).
- Y. Liu, A. M. Rollins, R. M. Levenson, F. Fereidouni, and M. W. Jenkins, “Pocket muse: an affordable, versatile and high-performance fluorescence microscope using a smartphone,” \JournalTitleCommunications biology 4, 334 (2021).
- H. Zhu, S. Mavandadi, A. F. Coskun, O. Yaglidere, and A. Ozcan, “Optofluidic fluorescent imaging cytometry on a cell phone,” \JournalTitleAnalytical chemistry 83, 6641–6647 (2011).
- A. Ganguli, A. Ornob, H. Yu, G. Damhorst, W. Chen, F. Sun, A. Bhuiya, B. Cunningham, and R. Bashir, “Hands-free smartphone-based diagnostics for simultaneous detection of zika, chikungunya, and dengue at point-of-care,” \JournalTitleBiomedical microdevices 19, 1–13 (2017).
- H. C. Koydemir, Z. Gorocs, D. Tseng, B. Cortazar, S. Feng, R. Y. L. Chan, J. Burbano, E. McLeod, and A. Ozcan, “Rapid imaging, detection and quantification of giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning,” \JournalTitleLab on a Chip 15, 1284–1293 (2015).
- K. Trofymchuk, V. Glembockyte, L. Grabenhorst, F. Steiner, C. Vietz, C. Close, M. Pfeiffer, L. Richter, M. L. Schütte, F. Selbach et al., “Addressable nanoantennas with cleared hotspots for single-molecule detection on a portable smartphone microscope,” \JournalTitleNature communications 12, 1–8 (2021).
- K. C. Lee, K. Lee, J. Jung, S. H. Lee, D. Kim, and S. A. Lee, “A smartphone-based fourier ptychographic microscope using the display screen for illumination,” \JournalTitleACS Photonics 8, 1307–1315 (2021).
- W. Lee, A. Upadhya, P. Reece, and T. G. Phan, “Fabricating low cost and high performance elastomer lenses using hanging droplets,” \JournalTitleBiomedical optics express 5, 1626–1635 (2014).
- N. A. Szydlowski, H. Jing, M. Alqashmi, and Y. S. Hu, “Cell phone digital microscopy using an oil droplet,” \JournalTitleBiomedical Optics Express 11, 2328–2338 (2020).
- B. Dai, Z. Jiao, L. Zheng, H. Bachman, Y. Fu, X. Wan, Y. Zhang, Y. Huang, X. Han, C. Zhao et al., “Colour compound lenses for a portable fluorescence microscope,” \JournalTitleLight: Science & Applications 8, 1–13 (2019).
- https://www.satzuma.com/product-page/smartphone-microscope.
- https://www.apexeloptic.com/product/200x-phone-microscope-lens/.
- C. Song, Y. Yang, X. Tu, Z. Chen, J. Gong, and C. Lin, “A smartphone-based fluorescence microscope with hydraulically driven optofluidic lens for quantification of glucose,” \JournalTitleIEEE Sensors Journal 21, 1229–1235 (2020).
- J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros, “Unpaired image-to-image translation using cycle-consistent adversarial networks,” in Proceedings of the IEEE international conference on computer vision, (2017), pp. 2223–2232.
- T. G. Chondros, “Archimedes life works and machines,” \JournalTitleMechanism and Machine Theory 45, 1766–1775 (2010).
- Y. Lu and J. Lu, “A universal approximation theorem of deep neural networks for expressing probability distributions,” \JournalTitleAdvances in neural information processing systems 33, 3094–3105 (2020).
- Y. Rivenson, H. Ceylan Koydemir, H. Wang, Z. Wei, Z. Ren, H. Günaydın, Y. Zhang, Z. Gorocs, K. Liang, D. Tseng et al., “Deep learning enhanced mobile-phone microscopy,” \JournalTitleAcs Photonics 5, 2354–2364 (2018).
- K. Kim and W. G. Lee, “Portable, automated and deep-learning-enabled microscopy for smartphone-tethered optical platform towards remote homecare diagnostics: A review,” \JournalTitleSmall Methods 7, 2200979 (2023).
- N. A. Switz, M. V. D’Ambrosio, and D. A. Fletcher, “Low-cost mobile phone microscopy with a reversed mobile phone camera lens,” \JournalTitlePloS one 9, e95330 (2014).
- https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix.
- J. G. Kidd and P. Rous, “A transplantable rabbit carcinoma originating in a virus-induced papilloma and containing the virus in masked or altered form,” \JournalTitleThe Journal of experimental medicine 71, 813–838 (1940).
- F. Pascale, J.-P. Pelage, M. Wassef, S. H. Ghegediban, J.-P. Saint-Maurice, T. De Baere, A. Denys, R. Duran, F. Deschamps, O. Pellerin et al., “Rabbit vx2 liver tumor model: a review of clinical, biology, histology, and tumor microenvironment characteristics,” \JournalTitleFrontiers in Oncology 12, 871829 (2022).
- Z. Zalevsky, “Extended depth of focus imaging: a review,” \JournalTitleSpie Reviews 1, 018001 (2010).
- E. Bo, Y. Luo, S. Chen, X. Liu, N. Wang, X. Ge, X. Wang, S. Chen, S. Chen, J. Li et al., “Depth-of-focus extension in optical coherence tomography via multiple aperture synthesis,” \JournalTitleOptica 4, 701–706 (2017).
- S. Abrahamsson, J. Chen, B. Hajj, S. Stallinga, A. Y. Katsov, J. Wisniewski, G. Mizuguchi, P. Soule, F. Mueller, C. D. Darzacq et al., “Fast multicolor 3d imaging using aberration-corrected multifocus microscopy,” \JournalTitleNature methods 10, 60–63 (2013).
- J. Yang, L. Liu, J. P. Campbell, D. Huang, and G. Liu, “Handheld optical coherence tomography angiography,” \JournalTitleBiomedical optics express 8, 2287–2300 (2017).
- S. A. Lee and C. Yang, “A smartphone-based chip-scale microscope using ambient illumination,” \JournalTitleLab on a Chip 14, 3056–3063 (2014).
- Y. L. Yap, S. L. Sing, and W. Y. Yeong, “A review of 3d printing processes and materials for soft robotics,” \JournalTitleRapid Prototyping Journal (2020).