Super-Resolution Lensless Imaging of Cells Using Brownian Motion

The lensless imaging technique, which integrates a microscope into a complementary metal oxide semiconductor (CMOS) digital image sensor, has become increasingly important for the miniaturization of biological microscope and cell detection equipment. However, limited by the pixel size of the CMOS im...

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Bibliographic Details
Published inApplied sciences Vol. 9; no. 10; p. 2080
Main Authors Fang, Yuan, Yu, Ningmei, Jiang, Yuquan
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.05.2019
Subjects
Algorithms
Brownian motion
Cell size
Diffraction
Fourier transforms
lensless imaging
Light emitting diodes
Methods
Noise
Registration
Signal to noise ratio
super-resolution
United States > US
California
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Summary:The lensless imaging technique, which integrates a microscope into a complementary metal oxide semiconductor (CMOS) digital image sensor, has become increasingly important for the miniaturization of biological microscope and cell detection equipment. However, limited by the pixel size of the CMOS image sensor (CIS), the resolution of a cell image without optical amplification is low. This is also a key defect with the lensless imaging technique, which has been studied by a many scholars. In this manuscript, we propose a method to improve the resolution of the cell images using the Brownian motion of living cells in liquid. A two-step algorithm of motion estimation for image registration is proposed. Then, the raw holographic images are reconstructed using normalized convolution super-resolution algorithm. The result shows that the effect of the collected cell image under the lensless imaging system is close to the effect of a 10× objective lens.
ISSN:2076-3417
2076-3417
DOI:10.3390/app9102080