
1.Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Division of Biomedical Engineering, Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
2.Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
3.INCoD – National Brazilian Institute for Digital Convergence/LAPIX, Image Processing and Computer Graphics Lab, Federal University of Santa Catarina, Brazil
4.Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Stanford University School of Medicine, Canary Center at Stanford for Cancer Early Detection, Palo Alto, CA, USA
5.Present Address: Department of Biomedical Engineering Faculty of Engineering, Başkent University, Ankara, Turkey
6.4VisionLab, Master in Applied Computing, University of Itajaí Valley, Brazil
7.CERTI Foundation, Florianopolis, Brazil
U Demirci. Email: utkan@stanford.edu
Published:2015-12,
Published Online:29 June 2015,
Received:25 December 2014,
Revised:12 June 2015,
Accepted:24 June 2015
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Sobieranski, A. C. et al. Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution. Light: Science & Applications, 4, e346 (2015).
Sobieranski, A. C. et al. Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution. Light: Science & Applications, 4, e346 (2015). DOI: 10.1038/lsa.2015.119.
In this paper
an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame processing. The samples are illuminated by a nearly coherent illumination system
where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging sensor. To increase the resolution
a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene
with small planar displacements. Displacements are resolved by a hybrid approach: (ⅰ) alignment of the LR images by a fast feature-based registration method
and (ⅱ) fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum solution. Numerical method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed sample. The presented approach was evaluated with various biological samples including sperm and platelets
whose dimensions are in the order of a few microns. The obtained results demonstrate a spatial resolution of 1.55 μm on a field-of-view of ≈30 mm
2
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digital in-line holographyimage registrationlensless imagingpoint-of-care platformpixel super-resolution
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