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Mechanical environment significantly affects the growth of tissue-engineered vessels. Previous studies have focused on the effect of pressure, while the effect of deformation has not been thoroughly investigated due to the lack of precise deformation control technologies. In this study, we have developed a vascular deformation control system using machine vision and feedback control algorithms. The system continuously perfuses the tissue-engineered vessel with a peristaltic pump. The real-time image of deformed vessel in the processing chamber was captured by a video camera and then transmitted to a machine vision identifier to analyze the diameter of the vessel. The time series of diameters formed deformation ratios, which was compared with the deformation set point (from 1% to 15% in this study). The feedback value was converted into analog signal, driving a control valve to regulate the resistance of the vascular outlet port. In the pulsate perfusion process, the deformation of the tissue-engineered vessels were, respectively, controlled at 1%, 3%, 5%, 7%, 10%, and 15%, with an average variation of only 0.03%. A video camera aided by machine vision module can identify the diameter of tissue-engineered vessels in high resolution. A simple feedback control system is enough for keeping the vascular deformation at any set point between 1% and 15%. These findings will guide further investigations on deformation-based mechanical stimuli in vascular tissue engineering.