Research On Real-time Monitoring Method Of Cell Physiological Activity Based On Lensless Imaging

The detection of cellular physiological activities in biological samples is of great significance in the fields of medical research,disease diagnosis,cytotoxicity research,and drug evaluation.Microscopic imaging systems are commonly used tools for observing cells.Despite the continuous progress in cell image detection methods,the research on real-time monitoring methods for cell physiological activities still faces many difficulties.An important reason is that these cell image detection devices cannot be separated from the interaction of multiple optical components such as lenses,making the entire imaging system bulky and cumbersome.At the same time,these optical imaging systems are complex to operate,further limiting the development of real-time cell monitoring.Lensless imaging technology avoids the shortcomings of traditional optical imaging technology,and the imaging systems based on lensless are small in size and light in weight.The lensless imaging technology of non-fluorescent materials can be divided into lensless shadow imaging and lensless digital holography imaging.Both methods can achieve cell imaging,but lensless digital holography imaging directly obtains cell holograms.The cells in the holograms are blurred,and clear images need to be obtained through the reconstruction algorithms,while lensless shadow imaging can directly capture clear cell images.This thesis aims to conduct research on real-time monitoring methods for cell physiological activities based on lensless shadow imaging technology.The main research contents are as follows:1.A microscopic imaging system is built based on lensless shadow imaging technology.The system uses a LED as the light source,uses an image sensor to capture cell sample images.Two reference-free image quality evaluation methods,image gradient and image contrast,are combined to study the conditions affecting the quality of lensless imaging and optimize the structural parameters of the imaging system to improve the imaging quality.2.Combining the advantages of microfluidic chips with low sample consumption and ease of integration with imaging systems,this thesis uses ultraviolet lithography technology to design and fabricate microfluidic chips for studying physiological activities of cells,builds a lensless on-chip imaging system to image HL60 cells and Hela cells,and uses image processing related algorithms to achieve automatic cell counting,with the counting error of less than 10%.An interface control program is developed based on the lensless imaging device to further improve the automation of cell counting.3.The cell migration simulation experiment is designed based on the lens-free imaging system,and the cell migration video is collected.The cell migration trajectory is tracked by a target tracking algorithm,and the average cell migration rate is detected.4.Through cell water swelling experiments,the lensless imaging results under the normal and water swelling states of the cells are captured.Support Vector Machine is used to achieve cell classification and detection for the above two states,with the test set accuracy of 96.7%.In addition,combined with image segmentation,physiological state detection of multiple cells in a single image is achieved.This thesis proposes a real-time monitoring method for cell physiological activity based on lensless imaging,which is of great significance for studying cell proliferation,cell migration process,and cell physiological status,and has important application value for developing real-time cell detection devices in the biomedical field.