Event-driven acquisition for content-enriched microscopy

Mahecic, Dora; Stepp, Willi L.; Zhang, Chen; Griffié, Juliette; Weigert, Martin; Manley, Suliana

doi:10.1038/s41592-022-01589-x

Cited by 50 publications

(36 citation statements)

References 57 publications

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“…Moreover, we are also optimistic about the extension of the two algorithms. The astonishing resolution enhancement and background inhibition of wide-field microscopy may be beneficial for some event-trigger microscopy setups 55,56 as they employ wide-field imaging to monitor cell activities and incorporating some analytical models to the deep-learning network 14,16 .…”

Section: Discussionmentioning

confidence: 99%

Noise-robust, physical microscopic deconvolution algorithm enabled by multi-resolution analysis regularization

Hou

Wang

et al. 2023

Preprint

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Despite the grand advances in fluorescence microscopy, the photon budget of fluorescent molecules remains the fundamental limiting factor for major imaging parameters, such as temporal resolution, duration, contrast, and even spatial resolution. Computational methods can strategically utilize the fluorescence photons against the imaging noise, to break the abovementioned limits. Here, we propose a multi-resolution analysis (MRA) approach to recharacterize and extract the two main characteristics of fluorescence images: (1) high contrast across the edge, and (2) high continuity along the edge. By regularizing the solution using framelet and curvelet domain sparsity, we develop MRA deconvolution algorithm for fluorescence image, which allows fine detail recovery even with negative signal-to-noise-ratio (SNR), and can provide more than 2-fold physical resolution enhancement with conspicuously fewer artifacts than maximum likelihood estimation (MLE) methods. Furthermore, we develop DeepMRA deconvolution algorithm that can provide computational background inhibition through a bias thresholding mechanism while deconvolving a fluorescence image. Compared with conventional background mitigation schemes, this novel deconvolution canonical form can deal with severer background and better preserve the high-frequency and low-intensity details, which are commonly disrupted by other algorithms. We demonstrate that the MRA and DeepMRA deconvolution algorithms can improve the SNR and resolution of biological images in various microscopies, such as wide-field, confocal, spinning-disk confocal (SD-confocal), light-sheet, structured illumination microscopy (SIM), and stimulated excitation depletion (STED) microscopy.

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Section: Discussionmentioning

confidence: 99%

Noise-robust, physical microscopic deconvolution algorithm enabled by multi-resolution analysis regularization

Hou

Wang

et al. 2023

Preprint

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“…In theory, the intensity-only SMOLM algorithm is also fast enough to be compatible with real-time processing, as a 200×200 pixel image (10×10 μm) with ~ 15 localizations takes about 10 ms to process, which is less than typical camera exposure times. This could enable molecular orientation event-triggered mi-croscopy (62, 63), something that would be extremely challenging if dipole PSF-fitting is required.…”

Section: Discussionmentioning

confidence: 99%

POLCAM: Instant molecular orientation microscopy for the life sciences

Bruggeman

Zhang

Needham

et al. 2023

Preprint

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Current methods for single-molecule orientation localization microscopy (SMOLM) require optical setups and algorithms that can be prohibitively slow and complex, limiting the widespread adoption for biological applications. We present POLCAM, a simplified SMOLM method based on polarized detection using a polarization camera, that can be easily implemented on any wide-field fluorescence microscope. To make polarization cameras compatible with single-molecule detection, we developed theory to minimize field-of-view errors, used simulations to optimize experimental design, and developed a fast algorithm based on Stokes parameter estimation which can operate over 1000 fold faster than the state of the art, enabling near-instant determination of molecular anisotropy. To aid in the adoption of POLCAM, we developed open-source image analysis software; a napari plugin for visualization of high-dimensional diffraction-limited polarization camera datasets, and a website detailing hardware installation and software use. To illustrate the potential of POLCAM in the life sciences, we applied our method to study both alpha-synuclein fibrils and the actin cytoskeleton of mammalian cells. To demonstrate that POLCAM also allows diffraction-limited imaging, we demonstrate POLCAM imaging actin in fibroblast-like cells and the plasma membrane of live human T cells.

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“…However, as discussed earlier, the phototoxicity considerations will determine the optimal image modality. Out of the super-resolution imaging techniques available, structured illumination microscopy (SIM) could be particularly well-suited, since it has moderate light exposure while still providing a twofold resolution improvement over conventional widefield techniques [ 130 , 131 ]. SICM microscopes are generally built on top of inverted optical microscopes, which makes combination of SICM with fluorescent techniques relatively straightforward.…”

Section: Label-free Methods For Long-term and High-resolution Imaging...mentioning

confidence: 99%

Label-Free Long-Term Methods for Live Cell Imaging of Neurons: New Opportunities

et al. 2023

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Time-lapse light microscopy combined with in vitro neuronal cultures has provided a significant contribution to the field of Developmental Neuroscience. The establishment of the neuronal polarity, i.e., formation of axons and dendrites, key structures responsible for inter-neuronal signaling, was described in 1988 by Dotti, Sullivan and Banker in a milestone paper that continues to be cited 30 years later. In the following decades, numerous fluorescently labeled tags and dyes were developed for live cell imaging, providing tremendous advancements in terms of resolution, acquisition speed and the ability to track specific cell structures. However, long-term recordings with fluorescence-based approaches remain challenging because of light-induced phototoxicity and/or interference of tags with cell physiology (e.g., perturbed cytoskeletal dynamics) resulting in compromised cell viability leading to cell death. Therefore, a label-free approach remains the most desirable method in long-term imaging of living neurons. In this paper we will focus on label-free high-resolution methods that can be successfully used over a prolonged period. We propose novel tools such as scanning ion conductance microscopy (SICM) or digital holography microscopy (DHM) that could provide new insights into live cell dynamics during neuronal development and regeneration after injury.

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Event-driven acquisition for content-enriched microscopy

Cited by 50 publications

References 57 publications

Noise-robust, physical microscopic deconvolution algorithm enabled by multi-resolution analysis regularization

Noise-robust, physical microscopic deconvolution algorithm enabled by multi-resolution analysis regularization

POLCAM: Instant molecular orientation microscopy for the life sciences

Label-Free Long-Term Methods for Live Cell Imaging of Neurons: New Opportunities

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