X-ray scatter tomography using coded apertures

This work proposes and studies a new field of x-ray tomography which combines the principles of scatter imaging and coded apertures, termed coded aperture x-ray scatter imaging (CAXSI). Conventional x-ray tomography reconstructs an object's electron density distribution by measuring a set of line integrals known as the x-ray transform, based physically on the attenuation of incident rays. More recently, scatter imaging has emerged as an alternative to attenuation imaging by measuring radiation from coherent and incoherent scattering. The information-rich scatter signal may be used to infer density as well as molecular structure throughout a volume. Some scatter modalities use collimators at the source and detector, resulting in long scan times due to the low efficiency of scattering mechanisms combined with a high degree of spatial filtering. CAXSI comes to the rescue by employing coded apertures. Coded apertures transmit a larger fraction of the scattered rays than collimators while also imposing structure to the scatter signal. In a coded aperture system each detector is sensitive to multiple ray paths, producing multiplexed measurements. The coding problem is then to design an aperture which enables de-multiplexing to reconstruct the desired physical properties and spatial distribution of the target. In this work, a number of CAXSI systems are proposed, analyzed, and demonstrated. One-dimensional pencil beams, two-dimensional fan beams, and three-dimensional cone beams are considered for the illumination. Pencil beam and fan beam CAXSI systems are demonstrated experimentally. The utility of energy-integrating (scintillation) detectors and energy-sensitive (photon counting) detectors are evaluated theoretically, and new coded aperture designs are presented for each beam geometry. Physical models are developed for each coded aperture system, from which resolution metrics are derived. Systems employing different combinations of beam geometry, coded apertures, and detectors are analyzed by constructing linear measurement operators and comparing their singular value decompositions. Since x-ray measurements are typically dominated by photon shot noise, iterative algorithms based on Poisson statistics are used to perform the reconstructions. This dissertation includes previously published and unpublished co-authored material.Doctor of Philosoph

Computational Cameras: Approaches, Benefits and Limits

A computational camera uses a combination of optics and software to produce images that cannot be taken with traditional cameras. In the last decade, computational imaging has emerged as a vibrant field of research. A wide variety of computational cameras have been demonstrated - some designed to achieve new imaging functionalities and others to reduce the complexity of traditional imaging. In this article, we describe how computational cameras have evolved and present a taxonomy for the technical approaches they use. We explore the benefits and limits of computational imaging, and describe how it is related to the adjacent and overlapping fields of digital imaging, computational photography and computational image sensors

Multi-Beam Scan Analysis with a Clinical LINAC for High Resolution Cherenkov-Excited Molecular Luminescence Imaging in Tissue.

Cherenkov-excited luminescence scanned imaging (CELSI) is achieved with external beam radiotherapy to map out molecular luminescence intensity or lifetime in tissue. Just as in fluorescence microscopy, the choice of excitation geometry can affect the imaging time, spatial resolution and contrast recovered. In this study, the use of spatially patterned illumination was systematically studied comparing scan shapes, starting with line scan and block patterns and increasing from single beams to multiple parallel beams and then to clinically used treatment plans for radiation therapy. The image recovery was improved by a spatial-temporal modulation-demodulation method, which used the ability to capture simultaneous images of the excitation Cherenkov beam shape to deconvolve the CELSI images. Experimental studies used the multi-leaf collimator on a clinical linear accelerator (LINAC) to create the scanning patterns, and image resolution and contrast recovery were tested at different depths of tissue phantom material. As hypothesized, the smallest illumination squares achieved optimal resolution, but at the cost of lower signal and slower imaging time. Having larger excitation blocks provided superior signal but at the cost of increased radiation dose and lower resolution. Increasing the scan beams to multiple block patterns improved the performance in terms of image fidelity, lower radiation dose and faster acquisition. The spatial resolution was mostly dependent upon pixel area with an optimized side length near 38mm and a beam scan pitch of P = 0.33, and the achievable imaging depth was increased from 14mm to 18mm with sufficient resolving power for 1mm sized test objects. As a proof-of-concept, in-vivo tumor mouse imaging was performed to show 3D rendering and quantification of tissue pO2 with values of 5.6mmHg in a tumor and 77mmHg in normal tissue

Fourier ptychography: current applications and future promises

Traditional imaging systems exhibit a well-known trade-off between the resolution and the field of view of their captured images. Typical cameras and microscopes can either “zoom in” and image at high-resolution, or they can “zoom out” to see a larger area at lower resolution, but can rarely achieve both effects simultaneously. In this review, we present details about a relatively new procedure termed Fourier ptychography (FP), which addresses the above trade-off to produce gigapixel-scale images without requiring any moving parts. To accomplish this, FP captures multiple low-resolution, large field-of-view images and computationally combines them in the Fourier domain into a high-resolution, large field-of-view result. Here, we present details about the various implementations of FP and highlight its demonstrated advantages to date, such as aberration recovery, phase imaging, and 3D tomographic reconstruction, to name a few. After providing some basics about FP, we list important details for successful experimental implementation, discuss its relationship with other computational imaging techniques, and point to the latest advances in the field while highlighting persisting challenges

Single-shot ultrafast optical imaging

Single-shot ultrafast optical imaging can capture two-dimensional transient scenes in the optical spectral range at ≥100 million frames per second. This rapidly evolving field surpasses conventional pump-probe methods by possessing real-time imaging capability, which is indispensable for recording nonrepeatable and difficult-to-reproduce events and for understanding physical, chemical, and biological mechanisms. In this mini-review, we survey state-of-the-art single-shot ultrafast optical imaging comprehensively. Based on the illumination requirement, we categorized the field into active-detection and passive-detection domains. Depending on the specific image acquisition and reconstruction strategies, these two categories are further divided into a total of six subcategories. Under each subcategory, we describe operating principles, present representative cutting-edge techniques, with a particular emphasis on their methodology and applications, and discuss their advantages and challenges. Finally, we envision prospects for technical advancement in this field