Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring
Type
ArticleAuthors
Wu, YichenOzcan, Aydogan

Date
2017-08-31Online Publication Date
2017-08-31Print Publication Date
2018-03Permanent link to this record
http://hdl.handle.net/10754/625803
Metadata
Show full item recordAbstract
Optical compound microscope has been a major tool in biomedical imaging for centuries. Its performance relies on relatively complicated, bulky and expensive lenses and alignment mechanics. In contrast, the lensless microscope digitally reconstructs microscopic images of specimens without using any lenses, as a result of which it can be made much smaller, lighter and lower-cost. Furthermore, the limited space-bandwidth product of objective lenses in a conventional microscope can be significantly surpassed by a lensless microscope. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable and cost-effective devices to potentially address various point-of-care, global-health and telemedicine related challenges. In this review, we discuss the operation principles and the methods behind lensless digital holographic on-chip microscopy. We also go over various applications that are enabled by cost-effective and compact implementations of lensless microscopy, including some recent work on air quality monitoring, which utilized machine learning for high-throughput and accurate quantification of particulate matter in air. Finally, we conclude with a brief future outlook of this computational imaging technology.Citation
Wu Y, Ozcan A (2017) Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring. Methods. Available: http://dx.doi.org/10.1016/j.ymeth.2017.08.013.Sponsors
The Ozcan Research Group at UCLA acknowledges the support of the Presidential Early Career Award for Scientists and Engineers (PECASE), the Army Research Office (ARO; W911NF-13-1-0419 and W911NF-13-1-0197), the ARO Life Sciences Division, the National Science Foundation (NSF) CBET Division Biophotonics Program, the NSF Emerging Frontiers in Research and Innovation (EFRI) Award, the NSF EAGER Award, NSF INSPIRE Award, NSF Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Program, Office of Naval Research (ONR), the National Institutes of Health (NIH), the Howard Hughes Medical Institute (HHMI), Vodafone Americas Foundation, the Mary Kay Foundation, Steven & Alexandra Cohen Foundation, and KAUST. This work is based upon research performed in a laboratory renovated by the National Science Foundation under Grant No. 0963183, which is an award funded under the American Recovery and Reinvestment Act of 2009 (ARRA).Publisher
Elsevier BVJournal
Methodsae974a485f413a2113503eed53cd6c53
10.1016/j.ymeth.2017.08.013