Automated Sorting of Rare Cells Based on Autofocusing Visual Feedback in Fluorescence Microscopy The research on rare cells makes a significant contribution to biology research and medical treatment for the application of diagnostic operation as well as prognoses treatment. Therefore, sorting them from heterogeneous mixtures is crucial and valuable. Traditional cell sorting methods featured with poor purity and recovery rate as well as limited flexibility, which are not ideal approaches for rare type. In this paper, we proposed a cell screening method based on automated microrobotic aspirationandplacement strategy under fluorescence microscope. An innovative autofocusing visual feedback (AVF) method is proposed for precise threedimensional (3D) locating of target cells. For depth detection, multiple depth from defocus (MDFD) method is adopted to solve symmetry problem and attain an average accuracy of 97.07%. For planar locating, Markov random field (MRF) based locating method is utilized to separate and locate the overlapped cells. The end actuator locating and realtime tracking are performed relying on normalized crosscorrelation (NCC) method. Experiential results show that our system collects rare cells (100 cells ml1) at a speed of 5 cells min1 with 90% purity and 75% recovery rate, which is valuable for biological and medical application.

Automated MacroMicro Manipulation for Robotic Microinjection with Computer Vision Extensive research efforts have been made toward automating the microinjection of biological cells by leveraging microrobotic technologies. However, to best knowledge of the authors, there is no report on the automation of the timeconsuming process: moving the injection tools (a micropipette, a grippers, etc.) and cells into the field of view (FOV) of microscope from the macro FOV(outside the microscopic FOV). This paper presents a novel macromicro conversion strategy, and a grid detection and positioning algorithm to automate the timeconsuming step of moving the injection tools and cells to the microscopic FOV. The proposed solution can free the technician from the laborious handeye coordination operations for moving the injection tools and cells to the target position within the microscopic FOV. Furthermore, this paper proposes an autofocusing algorithm to automate the operation step: moving down the gripper from the air outside the culture media and then precisely clamping a cell in the liquid environment for injection. In the proposed solution, the active windowbased autofocusing algorithm is developed to solve the challenging problem: the image information is lost due to the xe2x80x9cviscous effectxe2x80x9d taking place when the gripper jaw touches the water surface. The proposed solutions are tested and validated by the microinjection experiments of zebrafish embryos using the inhouse develop microrobotic system. The technologies and strategies proposed in this paper significantly improve the automation level of the cell microinjections, and can be easily extended to any other micromanipulation of biological cells.