Cell segmentation and pipette identification for automated patch clamp recording

Yang, Runhuai; Tam, Chi Ho; Cheung, Ka Lun; Wong, Kai Chun; Xi, Ning; Yang, Jie; Lai, King Wai Chiu

doi:10.1186/s40638-014-0020-5

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…Different label-free pipette detection algorithms were compared previously 21 . Some automated patch clamp systems already contain pipette detection algorithms, e.g., intensity clustering 11 or thresholding-based 22 for fluorescence imaging, or Hough transform-based 23 for DIC optics. The other crucial step is the automatic detection of the cells which has only been performed in two-photon images so far.…”

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confidence: 99%

Automatic deep learning-driven label-free image-guided patch clamp system

et al. 2021

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Patch clamp recording of neurons is a labor-intensive and time-consuming procedure. Here, we demonstrate a tool that fully automatically performs electrophysiological recordings in label-free tissue slices. The automation covers the detection of cells in label-free images, calibration of the micropipette movement, approach to the cell with the pipette, formation of the whole-cell configuration, and recording. The cell detection is based on deep learning. The model is trained on a new image database of neurons in unlabeled brain tissue slices. The pipette tip detection and approaching phase use image analysis techniques for precise movements. High-quality measurements are performed on hundreds of human and rodent neurons. We also demonstrate that further molecular and anatomical analysis can be performed on the recorded cells. The software has a diary module that automatically logs patch clamp events. Our tool can multiply the number of daily measurements to help brain research.

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confidence: 99%

Automatic deep learning-driven label-free image-guided patch clamp system

et al. 2021

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“…Based on the electrical equivalent model, a conceptual control strategy for the microinjection was considered, as shown in Figure 9 . Firstly, the position of the cell and pipette were obtained via the visual-based cell and pipette segmentation process, which was developed in our group [ 30 ]. Subsequently, the pipette was manipulated to a position on the boundary of the cells, and the automated in vivo whole patch clamping process was then started, which was also developed in our group [ 31 ].…”

Section: The Current Response Of the Cell Cytoplasmic Microinjectimentioning

confidence: 99%

Development of the Electric Equivalent Model for the Cytoplasmic Microinjection of Small Adherent Cells

2017

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A novel approach utilizing current feedback for the cytoplasmic microinjection of biological cells is proposed. In order to realize the cytoplasmic microinjection on small adherent cells (diameter < 30 μm and thickness < 10 μm), an electrical model is built and analyzed according to the electrochemical properties of target cells. In this study, we have verified the effectiveness of the current measurement for monitoring the injection process and the study of ion channel activities for verifying the cell viability of the cells after the microinjection.

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Section: Introductionmentioning

confidence: 99%

Organic Bioelectronics for In Vitro Systems

et al. 2021

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Bioelectronics have made strides in improving clinical diagnostics and precision medicine. The potential of bioelectronics for bidirectional interfacing with biology through continuous, label-free monitoring on one side and precise control of biological activity on the other has extended their application scope to in vitro systems. The advent of microfluidics and the considerable advances in reliability and complexity of in vitro models promise to eventually significantly reduce or replace animal studies, currently the gold standard in drug discovery and toxicology testing. Bioelectronics are anticipated to play a major role in this transition offering a much needed technology to push forward the drug discovery paradigm. Organic electronic materials, notably conjugated polymers, having demonstrated technological maturity in fields such as solar cells and light emitting diodes given their outstanding characteristics and versatility in processing, are the obvious route forward for bioelectronics due to their biomimetic nature, among other merits. This review highlights the advances in conjugated polymers for interfacing with biological tissue in vitro, aiming ultimately to develop next generation in vitro systems. We showcase in vitro interfacing across multiple length scales, involving biological models of varying complexity, from cell components to complex 3D cell cultures. The state of the art, the possibilities, and the challenges of conjugated polymers toward clinical translation of in vitro systems are also discussed throughout.

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Cell segmentation and pipette identification for automated patch clamp recording

Cited by 4 publications

References 27 publications

Automatic deep learning-driven label-free image-guided patch clamp system

Automatic deep learning-driven label-free image-guided patch clamp system

Development of the Electric Equivalent Model for the Cytoplasmic Microinjection of Small Adherent Cells

Organic Bioelectronics for In Vitro Systems

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