Application of Improved GS Algorithm In Cell Computing Holography

Abstract

Background: As an important research direction in cell image processing, Computer Hologram(CH) can quantitatively detect and analyze the amplitude and phase information of cells and holographic reconstruct the recorded images. Compared with the traditional optical microscope, CH reduces the complexity of operation, avoids the operation of cell staining and does not affect the physiological characteristics of cells in the recording process. It plays an important role in the field of cell morphology measurement and deformation analysis. Results: An improved Gerchberg-Saxton (GS) algorithm is proposed to reconstruct cell hologram based on phase information. The cell image reconstructed by GS Algorithm with phase restricted conditions are analyzed and compared. Through the comparative experiments of different models, it shows that the improved GS algorithm is better than the traditional GS algorithm in cell image reconstruction based on phase information. With the improved algorithm of phase mapping and normalization conditions, the reconstructed image can distinguish the cell edge information and high signal-to-noise ratio information. The urine sediment image is taken as the experimental object. After reconstruction by this algorithm, other impurity cells can be filtered out, and the aberrant red blood cell image with clear edge can be obtained. This improved algorithm provides a new application for cell detection in clinical diagnosis.Conclusions: The phase map reflects the temporal and spatial information of the image, determines the time or spatial position where different frequency signals appear, and describes the overall shape of the object. Due to biological cells generally for phase type or class phase objects, the improved GS algorithm in this paper can well describe the phase information of restored image, which is more suitable for the practical application of cell phase reconstruction.