Super-Resolution Lensless Imaging of Cells Using Brownian Motion

Yuan Fang,Yuquan Jiang,Ningmei Yu

doi:10.3390/app9102080

Abstract

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.

Highlights

Since the late 2000s, the lensless imaging technique based on complementary metal oxide semiconductor (CMOS) image sensor (CIS) has enabled the creation of integrated microscopes on a chip scale [1,2]
According to the characteristics of Brownian motion direction and random displacement, we present a super-resolution method for a lensless imaging system based on Brownian motion
The cell images obtained by the lensless imaging system were registered using two-step motion estimation

Summary

Introduction

Since the late 2000s, the lensless imaging technique based on CIS has enabled the creation of integrated microscopes on a chip scale [1,2]. Using this technique to collect cell micrographic images has become a novel technique in the cell analysis aspect of point-of-care testing (POCT), which plays an important role in biological research, disease diagnosis, and new drug development [3,4,5,6,7,8,9]. The Ozcan research group (University of California) irradiated cell samples using a near-coherent light source to obtain holographic images and reconstruct the focused images using an iterative algorithm [14,15,16,17,18,19,20,21,22]

Methods

Results

Conclusion