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To enhance the AR user experience, an automated method for calibrating and dynamically registering deformable tissues is proposed. First, an automatic calibration method is proposed to help register the target tissue from the virtual to the real world. The calibration method is based on a 6D pose estimator, which is built on the feature\u2010matching network, SuperGlue and the depth estimation network, Metric3D. Subsequently, a dynamic registration method is proposed to track the deformation of the target tissue in real\u2010time. Moreover, a piece of cloth is utilized for four automatic calibration trials, resulting in a mean absolute error (MAE) of calibration accuracy at 3.79\u2009\u00b1\u20090.64\u2009mm. The dynamic registration accuracy is also assessed by varying the deformation of the target, yielding an MAE of 6.03\u2009\u00b1\u20090.96\u2009mm. 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