Abstract
Intracellular micromanipulation assisted by robotic systems has valuable applications in biomedical research, such as genetic diagnosis and genome-editing tasks. However, current studies suffer from a low success rate and a large operation damage because of insufficient information on the operation information of targeted specimens. The complexity of the intracellular environment causes difficulties in visualizing manipulation tools and specimens. This review summarizes and analyzes the current development of advanced biological imaging sampling and computational processing methods in intracellular micromanipulation applications. It also discusses the related limitations and future extension, providing an important reference about this field.
Highlights
Intracellular organelles and molecules governing the liveness [1,2], dynamics [3,4], organizations [5,6], and functionalization [7,8] at cellular, multicellular, and tissue levels have attracted considerable interests from the field of biomedical research
Imaging sampling is essential for a successful intracellular micromanipulation through which the recognition, localization, tracking, reconstruction, motion, and orientation control of target specimens and manipulation tools heavily rely on the quality of sampled images
This section mainly focuses on advanced biological imaging technologies at a cellular or subcellular level, such as commercially available state-of-the-art microscopes, including confocal fluorescence microscope (CFM), two-photon fluorescence microscope (TPFM), light sheet fluorescence microscope (LSFM), lab-built photoacoustic microscope (PAM), traditional wide-field fluorescence microscope (WFFM), advanced structured illumination microscope (SIM), and stimulated emission depletion microscope (STEDM) with a super-resolution imaging ability
Summary
Intracellular organelles and molecules governing the liveness [1,2], dynamics [3,4], organizations [5,6], and functionalization [7,8] at cellular, multicellular, and tissue levels have attracted considerable interests from the field of biomedical research. The acquired position should be precisely manipulated through computational imaging during intracellular operations. Optical observation should be carried out several times to ensure that the imaging plane contains the target organelles because of the random distribution [37]. Apart from the automation demand of existing intracellular micromanipulation systems, two main challenges are encountered in current studies: how to obtain the sampled images of targeted intracellular specimens with high resolution and contrast and how to precisely extract operation information from the sampled images for a successful intracellular micromanipulation. Many intelligent image computational processing methods have been proposed to restore the sampled images, analyze the targeted specimens, and provide precise visual feedback. Reviews on biological imaging and computational processing methods in intracellular micromanipulation applications are rarely reported. The intelligent computational image processing methods of the sampled images in different intracellular micromanipulation tasks are discussed and analyzed. This systematic summary of this field can provide valuable references for academic and industrial fields
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