Limited time-resolution in microscopy is an obstacle to many biological studies. Despite recent advances in hardware, digital cameras have limited operation modes that constrain frame-rate, integration time, and color sensing patterns. In this paper, we propose an approach to extend the temporal resolution of a conventional digital color camera by leveraging a multi-color illumination source. Our method allows for the imaging of single-hue objects at an increased frame-rate by trading spectral for temporal information (while retaining the ability to measure base hue). It also allows rapid switching to standard RGB acquisition. We evaluated the feasibility and performance of our method via experiments with mobile resolution targets. We observed a time-resolution increase by a factor 2.8 with a threefold increase in temporal sampling rate. We further illustrate the use of our method to image the beating heart of a zebrafish larva, allowing the display of color or fast grayscale images. Our method is particularly well-suited to extend the capabilities of imaging systems where the flexibility of rapidly switching between high frame rate and color imaging are necessary.
State-of-the-art acoustic models for Automatic Speech Recognition (ASR) are based on Hidden Markov Models (HMM) and Deep Neural Networks (DNN) and often require thousands of hours of transcribed speech data during training. Therefore, building multilingual ASR systems or systems on a language with few resources is a challenging task. Multilingual training and cross-lingual adaptation are potential solutions. However, context-dependent states modeling creates difficulties for multilingual and cross-lingual ASR because of the large increase in context dependent labels arising from the phone set mismatch.
Generalized sampling is a flexible framework for signal acquisition, which relaxes the need for ideal pre-filters. Nevertheless, implementation remains challenging for dynamic imaging applications because it requires simultaneously measuring multiple overlapping inner-products and because only positive signals (intensities) can be measured by cameras. We present a method to collect videos of monochromatic objects by projecting the incoming signal at each pixel in a temporal B-spline space of degree 0, 1, or 2 by using a conventional RGB camera and a modulated three-color light source for illumination. Specifically, we solve the basis function overlap problem by multiplexing the acquisition in different color ranges and use B-spline pieces (which are positive) as projection kernels of a biorthogonal projection-expansion bases pair. The steps to recover signal samples include spectral unmixing and inverse filtering. Reconstructions we obtained from simulated and experimentally-acquired microscopy data demonstrate the feasibility of our approach.
Studying dynamic biological processes, such as heart development and function in zebrafish embryos, often relies on multi-channel fluorescence labeling to distinguish multiple anatomical features, yet also demands high frame rates to capture rapid cell motions. Although a recently proposed method for imaging dynamic samples in transmission or reflection allows to conveniently switch between color imaging or boosting the frame rate by use of spectrally-encoded, temporally-modulated illumination sequences and a hue-encoded shutter (hue-encode shutter method, HESM), the technique is not applicable directly in fluorescence microscopy, where the emitted light spectrum is mostly independent of the excitation wavelength. In this paper, we extend HESM by using samples labeled with multiple fluorophores, whose emission signal can either be used to distinguish multiple anatomical features when imaged in multi-channel mode or, if the fluorophores are co-localized in a dynamic tissue, to increase the frame rate via HESM. We detail the necessary steps to implement this method in a two-color light-sheet microscope to image the beating heart of a zebrafish embryo. Specifically, we propose an adapted laser modulation scheme for illumination, we identify caveats in choosing a suitable multi-color fluorophore labeling strategy, and derive an ℓ1-regularized reconstruction technique that is sufficiently robust to handle the low signal-to-noise ratio and labeling inhomogeneities in the fluorescence images at hand. Using the case of a beating heart in a zebrafish embryo, we experimentally show an increase in the frame rate by a factor two while preserving the ability to image static features labeled in distinct channels, thereby demonstrating the applicability of HESM to fluorescence. With a suitable illumination setup and fluorescent labeling, the method could generalize to other applications where flexibility between multiple channel and high-speed fluorescence imaging is desirable. For fluorophores that are not co-localized, the imaging system is similar to a conventional light sheet microscope.
Significance: Despite recent developments in microscopy, temporal aliasing can arise when imaging dynamic samples. Modern sampling frameworks, such as generalized sampling, mitigate aliasing but require measurement of temporally overlapping and potentially negative-valued inner products. Conventional cameras cannot collect these directly as they operate sequentially and are only sensitive to light intensity. Aim: We aim to mitigate aliasing in microscopy of dynamic monochrome samples by implementing generalized sampling via the use of a color camera and modulated color illumination. Approach: We solve the overlap problem by spectrally multiplexing the acquisitions and using (positive) B-spline segments as projection kernels. Reconstruction involves spectral unmixing and inverse filtering. We implemented this method using a color LED illuminator. We evaluated its performance by imaging a rotating grid and its applicability by imaging the beating zebrafish embryo heart in transmission and light-sheet microscopes. Results: Compared to stroboscopic imaging, our method mitigates aliasing with performance improving as the projection order increases. The approach can be implemented in conventional microscopes but is limited by the number of available LED colors and camera channels. Conclusions: Generalized sampling can be implemented via color modulation in microscopy to mitigate temporal aliasing. The simple hardware requirements could make it applicable to other optical imaging modalities.
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