Accelerated High-Resolution Photoacoustic Tomography via Compressed Sensing

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue. A particular example is the planar Fabry-Perot (FP) scanner, which yields high-resolution images but takes several minutes to sequentially map the photoacoustic field on the sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: First, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP scanner and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in-vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction methods that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of PAT scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.Comment: submitted to "Physics in Medicine and Biology

A versatile maskless microscope projection photolithography system and its application in light-directed fabrication of DNA microarrays

We present a maskless microscope projection lithography system (MPLS), in which photomasks have been replaced by a Digital Micromirror Device type spatial light modulator (DMD, Texas Instruments). Employing video projector technology high resolution patterns, designed as bitmap images on the computer, are displayed using a micromirror array consisting of about 786000 tiny individually addressable tilting mirrors. The DMD, which is located in the image plane of an infinity corrected microscope, is projected onto a substrate placed in the focal plane of the microscope objective. With a 5x(0.25 NA) Fluar microscope objective, a fivefold reduction of the image to a total size of 9 mm2 and a minimum feature size of 3.5 microns is achieved. Our system can be used in the visible range as well as in the near UV (with a light intensity of up to 76 mW/cm2 around the 365 nm Hg-line). We developed an inexpensive and simple method to enable exact focusing and controlling of the image quality of the projected patterns. Our MPLS has originally been designed for the light-directed in situ synthesis of DNA microarrays. One requirement is a high UV intensity to keep the fabrication process reasonably short. Another demand is a sufficient contrast ratio over small distances (of about 5 microns). This is necessary to achieve a high density of features (i.e. separated sites on the substrate at which different DNA sequences are synthesized in parallel fashion) while at the same time the number of stray light induced DNA sequence errors is kept reasonably small. We demonstrate the performance of the apparatus in light-directed DNA chip synthesis and discuss its advantages and limitations.Comment: 12 pages, 9 figures, journal articl

System calibration method for Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a recently proposed quantitative phase imaging technique with high resolution and wide field-of-view (FOV). In current FPM imaging platforms, systematic error sources come from the aberrations, LED intensity fluctuation, parameter imperfections and noise, which will severely corrupt the reconstruction results with artifacts. Although these problems have been researched and some special methods have been proposed respectively, there is no method to solve all of them. However, the systematic error is a mixture of various sources in the real situation. It is difficult to distinguish a kind of error source from another due to the similar artifacts. To this end, we report a system calibration procedure, termed SC-FPM, based on the simulated annealing (SA) algorithm, LED intensity correction and adaptive step-size strategy, which involves the evaluation of an error matric at each iteration step, followed by the re-estimation of accurate parameters. The great performance has been achieved both in simulation and experiments. The reported system calibration scheme improves the robustness of FPM and relaxes the experiment conditions, which makes the FPM more pragmatic.Comment: 18 pages, 9 figure

Adaptive optics wavefront compensation for solid immersion microscopy in backside imaging

Thesis (Ph.D.)--Boston UniversityThis dissertation concerns advances in high-resolution optical microscopy needed to detect faults in next generation semiconductor chips. In this application, images are made through the chips' back side to avoid opaque interconnect metal layers on the frontside. Near infrared wavelengths are required, since the silicon is relatively transparent at these wavelengths. A significant challenge in this technique is to resolve features as small as 200nm using wavelengths exceeding 1OOOnm. The highest imaging resolution achievable with refractive optics at infrared wavelengths is demonstrated in this dissertation using an aplanatic solid immersion lens (SIL). This is the only method that has been found to be of sufficient resolution to image the next generation of integrated circuits. While the use of an aplanatic solid immersion lens theoretically allows numerical aperture far in excess of conventional microscopy (NASIL ~ 3.5), it also makes the system performance particularly sensitive to aberrations, especially when the samples have thicknesses that are more than a few micrometers thicker or thinner than designed thickness, or when the refractive index of the SIL is slightly different than that of the sample. In the work described here, practical design considerations of the SILs are examined. A SIL-based confocal scanning microscope system is designed and constructed. The aberrations of the system due to thickness uncertainty and material mismatch are simulated using both analytical model and ray-tracing software, and are measured in the SIL experimental apparatus. The dominant aberration for samples with thickness mismatch is found to be spherical aberration. Wavefront errors are compensated by a microelectromechanical systems deformable mirror (MEMS DM) in the optical system's pupil. The controller is implemented either with closed-loop real time sensor feedback or with predictive open-loop estimation of optical aberrations. Different DM control algorithms and aberration compensation techniques are studied and compared. The experimental results agree well with simulation and it has been demonstrated through models and experiments in this work that the stringent sample thickness tolerances previously needed for high numerical aperture SIL microcopy can be relaxed considerably through aberration compensation. Near-diffraction-limited imaging performance has been achieved in most cases that correspond to practical implementation of the technique

Deep imaging inside scattering media through virtual spatiotemporal wavefront shaping

The multiple scattering of light makes materials opaque and obstructs imaging. Optimized wavefronts can overcome scattering to focus but typically require restrictive guidestars and only work within an isoplanatic patch. Focusing by lenses and wavefront shaping by spatial light modulators also limit the imaging volume and update speed. Here, we introduce scattering matrix tomography (SMT): use the measured scattering matrix of the sample to construct its volumetric image by scanning a confocal spatiotemporal focus with input and output wavefront correction for every isoplanatic patch, dispersion compensation, and index-mismatch correction--all performed digitally during post-processing without a physical guidestar. The digital focusing offers a large depth of field without constraint by the focal plane's Rayleigh range, and the digital wavefront correction enables image optimization with fast updates unrestricted by the speed of the hardware. We demonstrate SMT with sub-micron diffraction-limited lateral resolution and one-micron bandwidth-limited axial resolution at one millimeter beneath ex vivo mouse brain tissue and inside a dense colloid, where conventional imaging methods fail due to the overwhelming multiple scattering. SMT translates deep-tissue imaging into a computational reconstruction and optimization problem. It is noninvasive and label-free, with prospective applications in medical diagnosis, biological science, colloidal physics, and device inspection

3D microwave tomography with huber regularization applied to realistic numerical breast phantoms

Quantitative active microwave imaging for breast cancer screening and therapy monitoring applications requires adequate reconstruction algorithms, in particular with regard to the nonlinearity and ill-posedness of the inverse problem. We employ a fully vectorial three-dimensional nonlinear inversion algorithm for reconstructing complex permittivity profiles from multi-view single-frequency scattered field data, which is based on a Gauss-Newton optimization of a regularized cost function. We tested it before with various types of regularizing functions for piecewise-constant objects from Institut Fresnel and with a quadratic smoothing function for a realistic numerical breast phantom. In the present paper we adopt a cost function that includes a Huber function in its regularization term, relying on a Markov Random Field approach. The Huber function favors spatial smoothing within homogeneous regions while preserving discontinuities between contrasted tissues. We illustrate the technique with 3D reconstructions from synthetic data at 2GHz for realistic numerical breast phantoms from the University of Wisconsin-Madison UWCEM online repository: we compare Huber regularization with a multiplicative smoothing regularization and show reconstructions for various positions of a tumor, for multiple tumors and for different tumor sizes, from a sparse and from a denser data configuration