Visuo-haptic virtual exploration of single cell morphology and mechanics based on AFM mapping in fast mode

Petit, Claudie; Kechiche, Marwene; Ivan, Ioan Alexandru; Toscano, Rosario; Bolcato, V.; Planus, Emmanuelle; Marchi, Florence

doi:10.1007/s12213-020-00140-5

Cited by 5 publications

(1 citation statement)

References 36 publications

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“…Some authors have already started to explore this path using vector representations ( Blanc et al, 2020 ). B) There is potential to improve the interaction between humans and VR/AR, using eye-tracking ( Günther et al, 2020 ) or through haptic interfaces ( Petit et al, 2020 ). For example, in more biophysical applications, while measuring forces in cells or multicellular systems using optical tweezers or microchips is widely used, kinesthetic communication could bring human perception by providing local sensations, which would further improve the selection of responses in a 3D + time space.…”

Section: Discussion/perspectivesmentioning

confidence: 99%

Challenges of intracellular visualization using virtual and augmented reality

et al. 2022

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Microscopy image observation is commonly performed on 2D screens, which limits human capacities to grasp volumetric, complex, and discrete biological dynamics. With the massive production of multidimensional images (3D + time, multi-channels) and derived images (e.g., restored images, segmentation maps, and object tracks), scientists need appropriate visualization and navigation methods to better apprehend the amount of information in their content. New modes of visualization have emerged, including virtual reality (VR)/augmented reality (AR) approaches which should allow more accurate analysis and exploration of large time series of volumetric images, such as those produced by the latest 3D + time fluorescence microscopy. They include integrated algorithms that allow researchers to interactively explore complex spatiotemporal objects at the scale of single cells or multicellular systems, almost in a real time manner. In practice, however, immersion of the user within 3D + time microscopy data represents both a paradigm shift in human-image interaction and an acculturation challenge, for the concerned community. To promote a broader adoption of these approaches by biologists, further dialogue is needed between the bioimaging community and the VR&AR developers.

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Section: Discussion/perspectivesmentioning

confidence: 99%

Challenges of intracellular visualization using virtual and augmented reality

et al. 2022

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An optimal gesture controlling of robotic system

Saxena¹,

Gupta²,

Mohsin³

et al. 2023

Materials Today: Proceedings

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Machine learning prediction models for AFM virtual imaging system

Yang

Liu

et al. 2023

J. Phys.: Conf. Ser.

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Nowadays, virtual laboratories are widely used in education and training in universities. Such virtual labs do gain some effect in teaching, assisting students to be familiar with the experimental steps. However, these systems tend to be relatively simple. There is room for improvement in helping students understand the experimental principles. This is particularly evident in the teaching of atomic force microscopy. In order to overcome these shortcomings of the AFM virtual laboratory, we present a virtual AFM imaging system with a lower-resolution contact mode. We restore the core principle of the beam deflection method in AFM using the unity3D development platform. Several machine learning techniques are employed to build an imaging prediction model. Since no public dataset is available for the task of prediction of topographical maps, we create the first dataset of grating samples for prediction. The result indicates that the proposed topographical map prediction model with the best performance is CatBoost. We prove the feasibility of building a virtual AFM imaging system with the ability to visualize internal structures and predict sample topographical maps. This work has important applications related to the 3D dynamic display of the AFM scanning and imaging process and user experience training. At the same time, it can help users get a preliminary understanding of the imaging effect of different types of experimental samples under AFM, providing a new idea for the construction of AFM virtual laboratories.

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Visuo-haptic virtual exploration of single cell morphology and mechanics based on AFM mapping in fast mode

Cited by 5 publications

References 36 publications

Challenges of intracellular visualization using virtual and augmented reality

Challenges of intracellular visualization using virtual and augmented reality

An optimal gesture controlling of robotic system

Machine learning prediction models for AFM virtual imaging system

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