Development Of Cell Viability Online Detection System Based On Image Processing Technology

In many researches of cell biology and medicine,cell viability assessment is a routine and indispensable step to quantificationally assess the response of cells to drugs and other biochemical stimuli.The traditional cell viability assessment,like MTT method,CCK-8 method(biochemical detection methods)and fluorescent staining method(optical detection method),inevitably requires to add some staining reagents or fluorescent reagents,which can lead to the change of the cell physiological function.Also,the process of assay,which requires many contrast reagents,is complicated,time-consuming and labor-intensive.Nowadays,label-free cell viability assessment becomes a frontier topic in this field.It is of great significance for biomedical research to develop an automated cell viability online detection device based on the new optical imaging technology and image processing technology.In this paper,a cell viability online detection device,which combines lensless diffraction imaging technology and digital image processing technology,is designed based on the analysis of the current status and insufficiency of cell viability online detection technology.The main research contents include the following aspects:(1)Proposed an overall scheme of cell viability online detection system based on the image processing technology,including lensless diffraction imaging module,cells image acquisition and transmission module and upper computer application module;(2)Designed an algorithm for automatic cell viability detection for lensless cells images.The algorithm includes image enhancement process,image feature extraction,cell number recognition,cell activity recognition and cell viability calculation;(3)Observed the process of cell death under microscope imaging platform and lensless imaging platform,analyzed and summarized the relationship between cell activity state and cell image characteristics.Extracted the shape characteristics,brightness characteristics and texture features of each cell according to the cell activity image feature analysis,and then built a soft measurement recognition model using LSSVM algorithm including cell number recognition model and cell activity recognition model;(4)Established cell viability online detection platform based on image processing technology,completed the relevant hardware circuit design and software control design,where hardware part includes lensless imaging module and USB control transmission module,software part includes cell image acquisition,transmission,display,storage and cell viability automatic identification process based on Open CV.(5)Verified the accuracy of online detection device for cell viability by performing the toxicity test of mouse liver cells with mercury chloride.In addition,the effectiveness of the cell viability online detection device was verified by comparing with CCK-8 method.The experimental results show: the designed cell viability online detection device,which is based on lensless diffraction imaging technology and image processing technology,was proved to well detect the cell viability.The detection results of this method are highly correlated with the results of CCK-8 method,that means an expected effect for image processing method to automatically recognize cell viability.