Simultaneous temporal superresolution and denoising for cardiac fluorescence microscopy

Due to low light emission of fluorescent samples, live fluorescence microscopy imposes a tradeoff between spatiotemporal resolution and signal-to-noise ratio. This can result in images and videos containing motion blur or Poisson-type shot noise, depending on the settings used during acquisition. Here, we propose an algorithm to simultaneously denoise and temporally super-resolve movies of repeating microscopic processes that is compatible with any conventional microscopy setup that can achieve imaging at a rate of at least twice that of the fundamental frequency of the process (above 4 frames per second for a 2 Hz process). Our method combines low temporal resolution frames from multiple cycles of a repeating process to reconstruct a denoised, higher temporal resolution image sequence which is the solution to a linear program that maximizes the consistency of the reconstruction with the measurements, under a regularization constraint. This paper describes, in particular, a parallelizable superresolution reconstruction algorithm and demonstrates its application to live cardiac fluorescence microscopy. Using our method, we experimentally show temporal resolution improvement by a factor of 1.6, resulting in a visible reduction of motion blur in both on-sample and off-sample frames

Computational Imaging Methods for Improving Resolution in Biological Microscopy

Optical microscopy is an essential tool for biological research, as it allows for non-invasive imaging of small animals. However, optical microscopy has its limits. Due to the low light level, fluorescence microscopy prohibits high speed imaging, making it difficult to study fast dynamic biological processes. In addition, optical blur due to the diffraction of light results in limited spatial resolution, particularly when using objective lenses with low numerical apertures. In this thesis, we propose computational imaging methods to overcome these limitations using a combination of novel image acquisition procedures and reconstruction algorithms.The first part of this thesis deals with improving temporal resolution in fluorescence microscopy to image rapid, repeating processes. We take advantage of multiple acquisitions, each taken with different time delays or temporally modulated illumination patterns, to recover high frequency information that is lost with traditional imaging. We demonstrate our method to image the beating heart in live embryonic zebrafish with reduced motion blur and high resolution in time.The second part of this thesis deals with reducing spatial blur in optical projection tomography, a form of optical microscopy that uses multiple 2D projections to reconstruct a 3D image of an object. We propose a method to reduce the optical distortion (as characterized by the system's optical point spread function) that can be implemented with a scanning acquisition approach combined with a modified filtered backprojection algorithm for reconstruction. We demonstrate our method to image blood vessels in larval zebrafish with high spatial resolution and reduced out-of-focus blur.The final part of this thesis deals with the dimensional limitation of 2D sensors for measuring 3D motion in microscopy. We propose a method to combine two-dimensional motion estimates from multiple views to recover out-of-plane velocity and reconstruct a divergence-free, three-dimensional velocity field. We demonstrate our method to measure, for the first time, dynamic blood flow in 3D inside the beating heart of a live zebrafish using optical microscopy.This thesis provides new tools that integrate custom image acquisition procedures and image reconstruction algorithms to overcome the resolution limitations -- temporal, spatial, and out-of-plane velocity resolution -- in optical microscopy. The methods presented in this thesis, in particular the single camera, active illumination method for temporal superresolution in fluorescence microscopy, will be directly applicable to a broad range of biological studies and will open up new perspectives for imaging small organisms in 3D (and time) with high spatio-temporal resolution

Single-molecule techniques in biophysics : a review of the progress in methods and applications

Single-molecule biophysics has transformed our understanding of the fundamental molecular processes involved in living biological systems, but also of the fascinating physics of life. Far more exotic than a collection of exemplars of soft matter behaviour, active biological matter lives far from thermal equilibrium, and typically covers multiple length scales from the nanometre level of single molecules up several orders of magnitude to longer length scales in emergent structures of cells, tissues and organisms. Biological molecules are often characterized by an underlying instability, in that multiple metastable free energy states exist which are separated by energy levels of typically just a few multiples of the thermal energy scale of kBT, where kB is the Boltzmann constant and T the absolute temperature, implying complex, dynamic inter-conversion kinetics across this bumpy free energy landscape in the relatively hot, wet environment of real, living biological matter. The key utility of single-molecule biophysics lies in its ability to probe the underlying heterogeneity of free energy states across a population of molecules, which in general is too challenging for conventional ensemble level approaches which measure mean average properties. Parallel developments in both experimental and theoretical techniques have been key to the latest insights and are enabling the development of highly-multiplexed, correlative techniques to tackle previously intractable biological problems. Experimentally, technological developments in the sensitivity and speed of biomolecular detectors, the stability and efficiency of light sources, probes and microfluidics, have enabled and driven the study of heterogeneous behaviours both in vitro and in vivo that were previously undetectable by ensemble methods..