Imaging extended single crystal lattice distortion fields with multi-peak Bragg ptychography.

Recent advances in phase-retrieval-based x-ray imaging methods have demonstrated the ability to reconstruct 3D distortion vector fields within a nanocrystal by using coherent diffraction information from multiple crystal Bragg reflections. However, these works do not provide a solution to the challenges encountered in imaging lattice distortions in crystals with significant defect content that result in phase wrapping. Moreover, these methods only apply to isolated crystals smaller than the x-ray illumination, and therefore cannot be used for imaging of distortions in extended crystals. We introduce multi-peak Bragg ptychography which addresses both challenges via an optimization framework that combines stochastic gradient descent and phase unwrapping methods for robust image reconstruction of lattice distortions and defects in extended crystals. Our work uses modern automatic differentiation toolsets so that the method is easy to extend to other settings and easy to implement in high-performance computers. This work is particularly timely given the broad interest in using the increased coherent flux in fourth-generation synchrotrons for innovative material research.

4th generation synchrotron source boosts crystalline imaging at the nanoscale.

New 4th-generation synchrotron sources, with their increased brilliance, promise to greatly improve the performances of coherent X-ray microscopy. This perspective is of major interest for crystal microscopy, which aims at revealing the 3D crystalline structure of matter at the nanoscale, an approach strongly limited by the available coherent flux. Our results, based on Bragg ptychography experiments performed at the first 4th-generation synchrotron source, demonstrate the possibility of retrieving a high-quality image of the crystalline sample, with unprecedented quality. Importantly, the larger available coherent flux produces datasets with enough information to overcome experimental limitations, such as strongly deteriorated scanning conditions. We show this achievement would not be possible with 3rd-generation sources, a limit that has inhibited the development of this otherwise powerful microscopy method, so far. Hence, the advent of next-generation synchrotron sources not only makes Bragg ptychography suitable for high throughput studies but also strongly relaxes the associated experimental constraints, making it compatible with a wider range of experimental set-ups at the new synchrotrons.

Revealing nano-scale lattice distortions in implanted material with 3D Bragg ptychography.

Small ion-irradiation-induced defects can dramatically alter material properties and speed up degradation. Unfortunately, most of the defects irradiation creates are below the visibility limit of state-of-the-art microscopy. As such, our understanding of their impact is largely based on simulations with major unknowns. Here we present an x-ray crystalline microscopy approach, able to image with high sensitivity, nano-scale 3D resolution and extended field of view, the lattice strains and tilts in crystalline materials. Using this enhanced Bragg ptychography tool, we study the damage helium-ion-irradiation produces in tungsten, revealing a series of crystalline details in the 3D sample. Our results lead to the conclusions that few-atom-large 'invisible' defects are likely isotropic in orientation and homogeneously distributed. A partially defect-denuded region is observed close to a grain boundary. These findings open up exciting perspectives for the modelling of irradiation damage and the detailed analysis of crystalline properties in complex materials.

Efficient ptychographic phase retrieval via a matrix-free Levenberg-Marquardt algorithm.

The phase retrieval problem, where one aims to recover a complex-valued image from far-field intensity measurements, is a classic problem encountered in a range of imaging applications. Modern phase retrieval approaches usually rely on gradient descent methods in a nonlinear minimization framework. Calculating closed-form gradients for use in these methods is tedious work, and formulating second order derivatives is even more laborious. Additionally, second order techniques often require the storage and inversion of large matrices of partial derivatives, with memory requirements that can be prohibitive for data-rich imaging modalities. We use a reverse-mode automatic differentiation (AD) framework to implement an efficient matrix-free version of the Levenberg-Marquardt (LM) algorithm, a longstanding method that finds popular use in nonlinear least-square minimization problems but which has seen little use in phase retrieval. Furthermore, we extend the basic LM algorithm so that it can be applied for more general constrained optimization problems (including phase retrieval problems) beyond just the least-square applications. Since we use AD, we only need to specify the physics-based forward model for a specific imaging application; the first and second-order derivative terms are calculated automatically through matrix-vector products, without explicitly forming the large Jacobian or Gauss-Newton matrices typically required for the LM method. We demonstrate that this algorithm can be used to solve both the unconstrained ptychographic object retrieval problem and the constrained "blind" ptychographic object and probe retrieval problems, under the popular Gaussian noise model as well as the Poisson noise model. We compare this algorithm to state-of-the-art first order ptychographic reconstruction methods to demonstrate empirically that this method outperforms best-in-class first-order methods: it provides excellent convergence guarantees with (in many cases) a superlinear rate of convergence, all with a computational cost comparable to, or lower than, the tested first-order algorithms.

Super-resolved live-cell imaging using random illumination microscopy.

Current super-resolution microscopy (SRM) methods suffer from an intrinsic complexity that might curtail their routine use in cell biology. We describe here random illumination microscopy (RIM) for live-cell imaging at super-resolutions matching that of 3D structured illumination microscopy, in a robust fashion. Based on speckled illumination and statistical image reconstruction, easy to implement and user-friendly, RIM is unaffected by optical aberrations on the excitation side, linear to brightness, and compatible with multicolor live-cell imaging over extended periods of time. We illustrate the potential of RIM on diverse biological applications, from the mobility of proliferating cell nuclear antigen (PCNA) in U2OS cells and kinetochore dynamics in mitotic S. pombe cells to the 3D motion of myosin minifilaments deep inside Drosophila tissues. RIM's inherent simplicity and extended biological applicability, particularly for imaging at increased depths, could help make SRM accessible to biology laboratories.

Using automatic differentiation as a general framework for ptychographic reconstruction.

Coherent diffraction imaging methods enable imaging beyond lens-imposed resolution limits. In these methods, the object can be recovered by minimizing an error metric that quantifies the difference between diffraction patterns as observed, and those calculated from a present guess of the object. Efficient minimization methods require analytical calculation of the derivatives of the error metric, which is not always straightforward. This limits our ability to explore variations of basic imaging approaches. In this paper, we propose to substitute analytical derivative expressions with the automatic differentiation method, whereby we can achieve object reconstruction by specifying only the physics-based experimental forward model. We demonstrate the generality of the proposed method through straightforward object reconstruction for a variety of complex ptychographic experimental models.

Joint estimation of object and probes in vectorial ptychography.

Vectorial ptychography has been recently introduced to reconstruct the Jones matrix of an anisotropic object by means of series of ptychographic measurements performed using a set of polarized illumination probes in conjugation with various analyzers. So far, the probes were assumed to be completely known (amplitude, wavefront, state of polarization), which is rarely the case in practice. Here we address the issue of the joint estimating of the set of polarized illumination probes together with the Jones matrix of an anisotropic object in vectorial ptychography. We propose an algorithm based on a conjugate gradient strategy. Experimental results are reported, showing an improvement on the object estimate, in addition to a precise reconstruction of the probes.

Two-photon speckle illumination for super-resolution microscopy.

We present a numerical study of a microscopy setup in which the sample is illuminated with uncontrolled speckle patterns and the two-photon excitation fluorescence is collected on a camera. We show that, using a simple deconvolution algorithm for processing the speckle low-resolution images, this wide-field imaging technique exhibits resolution significantly better than that of two-photon excitation scanning microscopy or one-photon excitation bright-field microscopy.

Quantitative imaging of anisotropic material properties with vectorial ptychography.

Following the recent establishment of the formalism of vectorial ptychography [Opt. Lett.40, 5144 (2015)OPLEDP0146-959210.1364/OL.40.005144], first measurements, to the best of our knowledge, are reported in the optical range, demonstrating the capability of the proposed method to map the four parameters of the Jones matrix of an anisotropic specimen, and therefore to quantify a wide range of optical material properties, including power transmittance, optical path difference, diattenuation, retardance, and fast-axis orientation.

Measuring Three-Dimensional Strain and Structural Defects in a Single InGaAs Nanowire Using Coherent X-ray Multiangle Bragg Projection Ptychography.

III-As nanowires are candidates for near-infrared light emitters and detectors that can be directly integrated onto silicon. However, nanoscale to microscale variations in structure, composition, and strain within a given nanowire, as well as variations between nanowires, pose challenges to correlating microstructure with device performance. In this work, we utilize coherent nanofocused X-rays to characterize stacking defects and strain in a single InGaAs nanowire supported on Si. By reconstructing diffraction patterns from the 21̅1̅0 Bragg peak, we show that the lattice orientation varies along the length of the wire, while the strain field along the cross-section is largely unaffected, leaving the band structure unperturbed. Diffraction patterns from the 011̅0 Bragg peak are reproducibly reconstructed to create three-dimensional images of stacking defects and associated lattice strains, revealing sharp planar boundaries between different crystal phases of wurtzite (WZ) structure that contribute to charge carrier scattering. Phase retrieval is made possible by developing multiangle Bragg projection ptychography (maBPP) to accommodate coherent nanodiffraction patterns measured at arbitrary overlapping positions at multiple angles about a Bragg peak, eliminating the need for scan registration at different angles. The penetrating nature of X-ray radiation, together with the relaxed constraints of maBPP, will enable the in operando imaging of nanowire devices.

Joint Reconstruction Strategy for Structured Illumination Microscopy With Unknown Illuminations.

The blind structured illumination microscopy strategy proposed by Mudry et al. is fully re-founded in this paper, unveiling the central role of the sparsity of the illumination patterns in the mechanism that drives super-resolution in the method. A numerical analysis shows that the resolving power of the method can be further enhanced with optimized one-photon or two-photon speckle illuminations. A much improved numerical implementation is provided for the reconstruction problem under the image positivity constraint. This algorithm rests on a new preconditioned proximal iteration faster than existing solutions, paving the way to 3D and real-time 2D reconstruction.

Improving the axial and lateral resolution of three-dimensional fluorescence microscopy using random speckle illuminations.

We consider a fluorescence microscope in which several three-dimensional images of a sample are recorded for different speckle illuminations. We show, on synthetic data, that by summing the positive deconvolution of each speckle image, one obtains a sample reconstruction with axial and transverse resolutions that compare favorably to that of an ideal confocal microscope.

Ptychography in anisotropic media.

This letter describes ptychography in the context of polarized light probing anisotropic specimen (i.e., showing properties of birefringence and/or diattenuation). We established an optimization strategy using a vectorial formalism. We propose a measurement scheme using a set of linearly polarized probes and linear polarization analyzers, which allows the retrieval of the full anisotropy map of the specimen.

Noise models for low counting rate coherent diffraction imaging.

Coherent diffraction imaging (CDI) is a lens-less microscopy method that extracts the complex-valued exit field from intensity measurements alone. It is of particular importance for microscopy imaging with diffraction set-ups where high quality lenses are not available. The inversion scheme allowing the phase retrieval is based on the use of an iterative algorithm. In this work, we address the question of the choice of the iterative process in the case of data corrupted by photon or electron shot noise. Several noise models are presented and further used within two inversion strategies, the ordered subset and the scaled gradient. Based on analytical and numerical analysis together with Monte-Carlo studies, we show that any physical interpretations drawn from a CDI iterative technique require a detailed understanding of the relationship between the noise model and the used inversion method. We observe that iterative algorithms often assume implicitly a noise model. For low counting rates, each noise model behaves differently. Moreover, the used optimization strategy introduces its own artefacts. Based on this analysis, we develop a hybrid strategy which works efficiently in the absence of an informed initial guess. Our work emphasises issues which should be considered carefully when inverting experimental data.

On global and local convergence of half-quadratic algorithms.

This paper provides original results on the global and local convergence properties of half-quadratic (HQ) algorithms resulting from the Geman and Yang (GY) and Geman and Reynolds (GR) primal-dual constructions. First, we show that the convergence domain of the GY algorithm can be extended with the benefit of an improved convergence rate. Second, we provide a precise comparison of the convergence rates for both algorithms. This analysis shows that the GR form does not benefit from a better convergence rate in general. Moreover, the GY iterates often take advantage of a low cost implementation. In this case, the GY form is usually faster than the GR form from the CPU time viewpoint.

Three-dimensional edge-preserving image enhancement for computed tomography.

Computed tomography (CT) images exhibit a variable amount of noise and blur, depending on the physical characteristics of the apparatus and the selected reconstruction method. Standard algorithms tend to favor reconstruction speed over resolution, thereby jeopardizing applications where accuracy is critical. In this paper, we propose to enhance CT images by applying half-quadratic edge-preserving image restoration (or deconvolution) to them. This approach may be used with virtually any CT scanner, provided the overall point-spread function can be roughly estimated. In image restoration, Markov random fields (MRFs) have proven to be very flexible a priori models and to yield impressive results with edge-preserving penalization, but their implementation in clinical routine is limited because they are often viewed as complex and time consuming. For these practical reasons, we focused on numerical efficiency and developed a fast implementation based on a simple three-dimensional MRF model with convex edge-preserving potentials. The resulting restoration method provides good recovery of sharp discontinuities while using convex duality principles yields fairly simple implementation of the optimization. Further reduction of the computational load can be achieved if the point-spread function is assumed to be separable. Synthetic and real data experiments indicate that the method provides significant improvements over standard reconstruction techniques and compares well with convex-potential Markov-based reconstruction, while being more flexible and numerically efficient.