Automated Dissection of Intact Single Cell From Tissue Using Robotic Micromanipulation System

Obtaining single cell from tissues is important for intersection of information and bioscience research. In this letter, a robotic framework based on micromanipulation system has been proposed, which can automatically and intelligently cut down single cells intact from tissue sections. The proposed method consists of several steps. An attention mechanism improved (AMI) tip localization neural network is proposed to detect and track the needle tip of micro-scale displacement end-effector within the limited field of view under microscopy. Then, the transformation matrix between the camera and coordinate system of the robot is calculated. And the cutting trajectory is generated and optimized. Finally, the end-effector is controlled to obtain intact single cells from tissues by model predictive control (MPC). The performance of the framework is verified in paraffin tissue sections dissection experiment which shows proposed framework is robust and precise enough to obtain an intact single cell. The error of autonomous single cell dissection is no more than 0.61 $\mu \text{m}$ .