Fast widefield techniques for fluorescence and phase endomicroscopy

Thesis (Ph.D.)--Boston UniversityEndomicroscopy is a recent development in biomedical optics which gives researchers and physicians microscope-resolution views of intact tissue to complement macroscopic visualization during endoscopy screening. This thesis presents HiLo endomicroscopy and oblique back-illumination endomicroscopy, fast widefield imaging techniques with fluorescence and phase contrast, respectively. Fluorescence imaging in thick tissue is often hampered by strong out-of-focus background signal. Laser scanning confocal endomicroscopy has been developed for optically-sectioned imaging free from background, but reliance on mechanical scanning fundamentally limits the frame rate and represents significant complexity and expense. HiLo is a fast, simple, widefield fluorescence imaging technique which rejects out-of-focus background signal without the need for scanning. It works by acquiring two images of the sample under uniform and structured illumination and synthesizing an optically sectioned result with real-time image processing. Oblique back-illumination microscopy (OBM) is a label-free technique which allows, for the first time, phase gradient imaging of sub-surface morphology in thick scattering tissue with a reflection geometry. OBM works by back-illuminating the sample with the oblique diffuse reflectance from light delivered via off-axis optical fibers. The use of two diametrically opposed illumination fibers allows simultaneous and independent measurement of phase gradients and absorption contrast. Video-rate single-exposure operation using wavelength multiplexing is demonstrated

Phase control and measurement in digital microscopy

The ongoing merger of the digital and optical components of the modern microscope is creating opportunities for new measurement techniques, along with new challenges for optical modelling. This thesis investigates several such opportunities and challenges which are particularly relevant to biomedical imaging. Fourier optics is used throughout the thesis as the underlying conceptual model, with a particular emphasis on three--dimensional Fourier optics. A new challenge for optical modelling provided by digital microscopy is the relaxation of traditional symmetry constraints on optical design. An extension of optical transfer function theory to deal with arbitrary lens pupil functions is presented in this thesis. This is used to chart the 3D vectorial structure of the spatial frequency spectrum of the intensity in the focal region of a high aperture lens when illuminated by linearly polarised beam. Wavefront coding has been used successfully in paraxial imaging systems to extend the depth of field. This is achieved by controlling the pupil phase with a cubic phase mask, and thereby balancing optical behaviour with digital processing. In this thesis I present a high aperture vectorial model for focusing with a cubic phase mask, and compare it with results calculated using the paraxial approximation. The effect of a refractive index change is also explored. High aperture measurements of the point spread function are reported, along with experimental confirmation of high aperture extended depth of field imaging of a biological specimen. Differential interference contrast is a popular method for imaging phase changes in otherwise transparent biological specimens. In this thesis I report on a new isotropic algorithm for retrieving the phase from differential interference contrast images of the phase gradient, using phase shifting, two directions of shear, and non--iterative Fourier phase integration incorporating a modified spiral phase transform. This method does not assume that the specimen has a constant amplitude. A simulation is presented which demonstrates good agreement between the retrieved phase and the phase of the simulated object, with excellent immunity to imaging noise

Phase control and measurement in digital microscopy

The ongoing merger of the digital and optical components of the modern microscope is creating opportunities for new measurement techniques, along with new challenges for optical modelling. This thesis investigates several such opportunities and challenges which are particularly relevant to biomedical imaging. Fourier optics is used throughout the thesis as the underlying conceptual model, with a particular emphasis on three--dimensional Fourier optics. A new challenge for optical modelling provided by digital microscopy is the relaxation of traditional symmetry constraints on optical design. An extension of optical transfer function theory to deal with arbitrary lens pupil functions is presented in this thesis. This is used to chart the 3D vectorial structure of the spatial frequency spectrum of the intensity in the focal region of a high aperture lens when illuminated by linearly polarised beam. Wavefront coding has been used successfully in paraxial imaging systems to extend the depth of field. This is achieved by controlling the pupil phase with a cubic phase mask, and thereby balancing optical behaviour with digital processing. In this thesis I present a high aperture vectorial model for focusing with a cubic phase mask, and compare it with results calculated using the paraxial approximation. The effect of a refractive index change is also explored. High aperture measurements of the point spread function are reported, along with experimental confirmation of high aperture extended depth of field imaging of a biological specimen. Differential interference contrast is a popular method for imaging phase changes in otherwise transparent biological specimens. In this thesis I report on a new isotropic algorithm for retrieving the phase from differential interference contrast images of the phase gradient, using phase shifting, two directions of shear, and non--iterative Fourier phase integration incorporating a modified spiral phase transform. This method does not assume that the specimen has a constant amplitude. A simulation is presented which demonstrates good agreement between the retrieved phase and the phase of the simulated object, with excellent immunity to imaging noise

Development and Implementation of Fully 3D Statistical Image Reconstruction Algorithms for Helical CT and Half-Ring PET Insert System

X-ray computed tomography: CT) and positron emission tomography: PET) have become widely used imaging modalities for screening, diagnosis, and image-guided treatment planning. Along with the increased clinical use are increased demands for high image quality with reduced ionizing radiation dose to the patient. Despite their significantly high computational cost, statistical iterative reconstruction algorithms are known to reconstruct high-quality images from noisy tomographic datasets. The overall goal of this work is to design statistical reconstruction software for clinical x-ray CT scanners, and for a novel PET system that utilizes high-resolution detectors within the field of view of a whole-body PET scanner. The complex choices involved in the development and implementation of image reconstruction algorithms are fundamentally linked to the ways in which the data is acquired, and they require detailed knowledge of the various sources of signal degradation. Both of the imaging modalities investigated in this work have their own set of challenges. However, by utilizing an underlying statistical model for the measured data, we are able to use a common framework for this class of tomographic problems. We first present the details of a new fully 3D regularized statistical reconstruction algorithm for multislice helical CT. To reduce the computation time, the algorithm was carefully parallelized by identifying and taking advantage of the specific symmetry found in helical CT. Some basic image quality measures were evaluated using measured phantom and clinical datasets, and they indicate that our algorithm achieves comparable or superior performance over the fast analytical methods considered in this work. Next, we present our fully 3D reconstruction efforts for a high-resolution half-ring PET insert. We found that this unusual geometry requires extensive redevelopment of existing reconstruction methods in PET. We redesigned the major components of the data modeling process and incorporated them into our reconstruction algorithms. The algorithms were tested using simulated Monte Carlo data and phantom data acquired by a PET insert prototype system. Overall, we have developed new, computationally efficient methods to perform fully 3D statistical reconstructions on clinically-sized datasets

Model and learning-based strategies for intensity diffraction tomography

Intensity Diffraction Tomography (IDT) is a recently developed quantitative phase imaging tool with significant potential for biological imaging applications. This modality captures intensity images from a scattering sample under diverse illumination and reconstructs the object's volumetric permittivity contrast using linear inverse scattering models. IDT requires no through-focus sample scans or exogenous contrast agents for 3D object recovery and can be easily implemented with a standard microscope equipped with an off-the-shelf LED array. These factors make IDT ideal for biological research applications where easily implementable setups providing native sample morphological information are highly desirable. Given this modality's recent development, IDT suffers from a number of limitations preventing its widespread adoption: 1) large measurement datasets with long acquisition times limiting its temporal resolution, 2) model-based constraints preventing the evaluation of multiple-scattering samples, and 3) low axial resolution preventing the recovery of fine axial structures such as organelles and other subcellular structures. These factors limit IDT to primarily thin, static objects, and its unknown accuracy and sensitivity metrics cast doubt on the technology's quantitative recovery of morphological features. This thesis addresses the limitations of IDT through advancements provided from model and learning-based strategies. The model-based advancements guide new computational illumination strategies for high volume-rate imaging as well as investigate new imaging geometries, while the learning-based enhancements to IDT present an efficient method for recovering multiple-scattering biological specimens. These advancements place IDT in the optimal position of being an easily implementable, computationally efficient phase imaging modality recovering high-resolution volumes of complex, living biological samples in their native state. We first discuss two illumination strategies for high-speed IDT. The first strategy develops a multiplexed illumination framework based on IDT's linear model enabling hardware-limited 4Hz volume-rate imaging of living biological samples. This implementation is hardware-agnostic, allowing for fast IDT to be added to any existing setup containing programmable illumination hardware. While sacrificing some reconstruction quality, this multiplexed approach recovers high-resolution features in live cell cultures, worms, and embryos highlighting IDT's potential across numerous ranges of biological imaging. Following this illumination scheme, we discuss a hardware-based solution for live sample imaging using ring-geometry LED arrays. Inspired from the linear model, this hardware modification optimally captures the object's information in each LED illumination allowing for high-quality object volumes to be reconstructed from as few as eight intensity images. This small image requirement allows IDT to achieve camera-limited 10Hz volume rate imaging of live biological samples without motion artifacts. We show the capabilities of this annular illumination IDT setup on live worm samples. This low-cost solution for IDT's speed shows huge implications for enabling any biological imaging lab to easily study the form and function of biological samples of interest in their native state. Next, we present a learning-based approach to expand IDT to recovering multiple-scattering samples. IDT's linear model provides efficient computation of an object's 3D volume but fails to recover quantitative information in the presence of highly scattering samples. We introduce a lightweight neural network architecture, trained only on simulated natural image-based objects, that corrects the linear model estimates and improves the recovery of both weakly and strongly scattering samples. This implementation maintains the computational efficiency of IDT while expanding its reconstruction capabilities allowing for more generic imaging of biological samples. Finally, we discuss an investigation of the IDT modality for reflection mode imaging. IDT traditionally captures only low axial resolution information because it cannot capture the backscattered fields from the object that contain rich information regarding the fine details of the object's axial structures. Here, we investigated whether a reflection-mode IDT implementation was possible for recovering high axial resolution structures from this backscattered light. We develop the model, imaging setup, and rigorously evaluate the reflection case in simulation and experiment to show the possibility for reflection IDT. While this imaging geometry ultimately requires a nonlinear model for 3D imaging, we show the technique provides enhanced sensitivity to the object's structures in a complementary fashion to transmission-based IDT

Development of swept, confocally-aligned planar excitation (SCAPE) microscopy for high-speed, volumetric imaging of biological tissue

With the wide-spread adoption of exogenous fluorescent indicators – and more recently genetically encoded fluorescent proteins – over the past two decades, there exists a diverse chemical toolkit with which to probe biological systems. Individual cell types and sub-cellular compartments can be targeted in an increasingly wide range of model organisms. However, imaging these samples is often an exercise in balancing the needs of any given experiment against the constraints of the chosen imaging technology. For example, a volume of brain tissue is host to neurons, glia, vascular compartments and red blood cells that all occupy discrete locations in 3D space, but must work together to support healthy organ function. Single-cell activity on the order of milliseconds can trigger downstream processes that unfold over the course of multiple seconds or even minutes. The development of a technique capable of providing depth-resolved, volumetric imaging with scalable spatiotemporal resolution is crucial to developing a proper understanding of such biological systems. Bottlenecks in the throughput of existing technologies stem from a combination of inefficient illumination and volume acquisition strategies, and insufficient sensor read-out speeds. Light sheet microscopy is a promising solution, but individual designs tend to be highly specialized to specific types of samples and do not easily adapt to a wide range of experimental settings. In this thesis, I detail my work in developing swept, confocally-aligned planar excitation (SCAPE) microscopy from a first-generation prototype into a versatile, easy-to-reproduce, easy-to-use system for high-speed, 3D imaging. The first chapter introduces the challenges of designing optical systems capable of high-speed, volumetric imaging. An introduction to design choices faced in the construction of fluorescence microscopes, and current approaches to 3D imaging are discussed. The second chapter describes the progression from the 1st to 2nd generation SCAPE system. Improvements made through ray-tracing models and an enhanced optomechanical design are described, and results from this system in a number of model organisms are presented. The third chapter presents results from a range of biological applications to which SCAPE microscopy has been applied. Work in imaging the zebrafish heart to demonstrate the system’s improved imaging speed, the C. elegans to show the system’s resolution, and finally a number of examples of large field-of-view and high-resolution structural imaging are all described. Finally, the fourth chapter concludes with an overview of the work that lies ahead to both further develop of SCAPE microscopy, as well as to bring the existing system’s strengths to bear in a wider range of environments