School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, Shaanxi Province, China.
PLoS One. 2020 Jun 25;15(6):e0235111. doi: 10.1371/journal.pone.0235111. eCollection 2020.
The lensless optical fluid microscopy is of great significance to the miniaturization, portability and low cost development of cell detection instruments. However, the resolution of the cell image collected directly is low, because the physical pixel size of the image sensor is the same order of magnitude as the cell size. To solve this problem, this paper proposes a super-resolution scanning algorithm using a dual-line array sensor and a microfluidic chip. For dual-line array sensor images, the multi-group velocity and acceleration of cells flowing through the line array sensor are calculated. Then the reconstruction model of the super-resolution image is constructed with variable acceleration. By changing the angle between the line array image sensor and the direction of cell flow, the super-resolution image scanning and reconstruction are achieved in both horizontal and vertical directions. In addition, it is necessary to study the row by row extraction algorithm for cell foreground image. In this paper, the dual-line array sensor is implemented by adjusting the acquisition window of the image sensor with a pixel size of 2.2μm. When the tilt angle is 21 degrees, the equivalent pixel size is 0.79μm, improved 2.8 times, and after de-diffraction its average size error was 3.249%. As the angle decreases, the image resolution is higher, but the amount of information is less. This super-resolution scanning algorithm can be integrated on the chip and used with a microfluidic chip to realize on-chip instrument.
无透镜光学流体显微镜对于细胞检测仪器的小型化、便携化和低成本化发展具有重要意义。然而，直接采集的细胞图像分辨率较低，因为图像传感器的物理像素尺寸与细胞尺寸处于同一数量级。为了解决这个问题，本文提出了一种使用双线阵传感器和微流控芯片的超分辨率扫描算法。对于双线阵传感器图像，计算流过线阵传感器的细胞的多组速度和加速度。然后，构建具有变速的超分辨率图像重建模型。通过改变线阵图像传感器与细胞流动方向之间的角度，可以在水平和垂直方向上实现超分辨率图像的扫描和重建。此外，还需要研究细胞前景图像的逐行提取算法。在本文中，通过调整像素尺寸为 2.2μm 的图像传感器的采集窗口来实现双线阵传感器。当倾斜角度为 21 度时，等效像素尺寸为 0.79μm，提高了 2.8 倍，经过去衍射后其平均尺寸误差为 3.249%。随着角度的减小，图像分辨率越高，但信息量越少。这种超分辨率扫描算法可以集成在芯片上，并与微流控芯片结合使用，实现芯片上的仪器。
