Research on Dual-Line Array Subpixel Scanning Imaging for IoMT-Based Blood Cell Analysis System

The Internet of Medical Things (IoMT) provides great convenience by closely connecting medical devices, doctors, and patients. In health management and disease diagnosis, the development of lensless imaging technology and microfluidics has provided important solutions for implementing the point-of-care testing (POCT) devices used to analyze blood cells. However, the low resolution is one of the significant problems, and the existing work has increased system and algorithmic complexity. We conceived an integrated sense-and-calculate chip for balance and proposed dual-line array subpixel scanning imaging (DL-SSI) for an IoMT-based blood cell acquisition and analysis device. In this article, the line-scan imaging model was derived first, and a background modeling method was proposed to eliminate systematic noise in scanned images. A subpixel displacement estimation method was proposed to calculate the cell’s transient flow velocity based on space-time compensation. The time complexity is reduced by 95.08% at typical value, and it is more friendly to the integrated sense-and-calculate chip in hardware. In the reconstruction and restoration, the interpolation theory of the scanned image was deduced, and both the autofocusing algorithm and phase iteration algorithm was optimized for the scanning reconstructed diffraction image. Finally, a lensless DL-SSI terminal was built for testing, and the theoretical minimum size is 44 mm $\times $ 44 mm $\times $ 71.8 mm. Sufficient experiments show that DL-SSI is feasible, effective, and superior for IoMT-based blood cell acquisition and analysis.