3D exemplar-based image inpainting in electron microscopy

In electron microscopy (EM) a common problem is the non-availability of data, which causes artefacts in reconstructions. In this thesis the goal is to generate artificial data where missing in EM by using exemplar-based inpainting (EBI). We implement an accelerated 3D version tailored to applications in EM, which reduces reconstruction times from days to minutes. We develop intelligent sampling strategies to find optimal data as input for reconstruction methods. Further, we investigate approaches to reduce electron dose and acquisition time. Sparse sampling followed by inpainting is the most promising approach. As common evaluation measures may lead to misinterpretation of results in EM and falsify a subsequent analysis, we propose to use application driven metrics and demonstrate this in a segmentation task. A further application of our technique is the artificial generation of projections in tiltbased EM. EBI is used to generate missing projections, such that the full angular range is covered. Subsequent reconstructions are significantly enhanced in terms of resolution, which facilitates further analysis of samples. In conclusion, EBI proves promising when used as an additional data generation step to tackle the non-availability of data in EM, which is evaluated in selected applications. Enhancing adaptive sampling methods and refining EBI, especially considering the mutual influence, promotes higher throughput in EM using less electron dose while not lessening quality.Ein häufig vorkommendes Problem in der Elektronenmikroskopie (EM) ist die Nichtverfügbarkeit von Daten, was zu Artefakten in Rekonstruktionen führt. In dieser Arbeit ist es das Ziel fehlende Daten in der EM künstlich zu erzeugen, was durch Exemplar-basiertes Inpainting (EBI) realisiert wird. Wir implementieren eine auf EM zugeschnittene beschleunigte 3D Version, welche es ermöglicht, Rekonstruktionszeiten von Tagen auf Minuten zu reduzieren. Wir entwickeln intelligente Abtaststrategien, um optimale Datenpunkte für die Rekonstruktion zu erhalten. Ansätze zur Reduzierung von Elektronendosis und Aufnahmezeit werden untersucht. Unterabtastung gefolgt von Inpainting führt zu den besten Resultaten. Evaluationsmaße zur Beurteilung der Rekonstruktionsqualität helfen in der EM oft nicht und können zu falschen Schlüssen führen, weswegen anwendungsbasierte Metriken die bessere Wahl darstellen. Dies demonstrieren wir anhand eines Beispiels. Die künstliche Erzeugung von Projektionen in der neigungsbasierten Elektronentomographie ist eine weitere Anwendung. EBI wird verwendet um fehlende Projektionen zu generieren. Daraus resultierende Rekonstruktionen weisen eine deutlich erhöhte Auflösung auf. EBI ist ein vielversprechender Ansatz, um nicht verfügbare Daten in der EM zu generieren. Dies wird auf Basis verschiedener Anwendungen gezeigt und evaluiert. Adaptive Aufnahmestrategien und EBI können also zu einem höheren Durchsatz in der EM führen, ohne die Bildqualität merklich zu verschlechtern

X-ray CT Image Reconstruction on Highly-Parallel Architectures.

Model-based image reconstruction (MBIR) methods for X-ray CT use accurate models of the CT acquisition process, the statistics of the noisy measurements, and noise-reducing regularization to produce potentially higher quality images than conventional methods even at reduced X-ray doses. They do this by minimizing a statistically motivated high-dimensional cost function; the high computational cost of numerically minimizing this function has prevented MBIR methods from reaching ubiquity in the clinic. Modern highly-parallel hardware like graphics processing units (GPUs) may offer the computational resources to solve these reconstruction problems quickly, but simply "translating" existing algorithms designed for conventional processors to the GPU may not fully exploit the hardware's capabilities. This thesis proposes GPU-specialized image denoising and image reconstruction algorithms. The proposed image denoising algorithm uses group coordinate descent with carefully structured groups. The algorithm converges very rapidly: in one experiment, it denoises a 65 megapixel image in about 1.5 seconds, while the popular Chambolle-Pock primal-dual algorithm running on the same hardware takes over a minute to reach the same level of accuracy. For X-ray CT reconstruction, this thesis uses duality and group coordinate ascent to propose an alternative to the popular ordered subsets (OS) method. Similar to OS, the proposed method can use a subset of the data to update the image. Unlike OS, the proposed method is convergent. In one helical CT reconstruction experiment, an implementation of the proposed algorithm using one GPU converges more quickly than a state-of-the-art algorithm converges using four GPUs. Using four GPUs, the proposed algorithm reaches near convergence of a wide-cone axial reconstruction problem with over 220 million voxels in only 11 minutes.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113551/1/mcgaffin_1.pd

Parallelized X-Ray Tracing with GPU Ray-Tracing Engine

X-ray diffraction tomography (XDT) is used to probe material composition of objects, providing improved contrast between materials compared to conventional transmission based computed tomography (CT). In this work, a small angle approximation to Bragg\u27s Equation of diffraction is coupled with parallelized computing using Graphics Processing Units (GPUs) to accelerate XDT simulations. The approximation gives rise to a simple yet useful proportionality between momentum transfer, radial distance of diffracted signal with respect to incoming beam\u27s location, and depth of material, so that ray tracing may be parallelized. NVIDIA\u27s OptiX ray-tracing engine, a parallelized pipeline for GPUs, is employed to perform XDT by tracing rays in a virtual space, (x,y,zv), where zv is a virtual distance proportional to momentum transfer. The advantage gained in this approach is that ray tracing in this domain requires only 3D surface meshes, yielding calculations without the need of voxels. The simulated XDT projections demonstrate high consistency with voxel models, with a normalized mean square difference less than 0.66%, and ray-tracing times two orders of magnitude less than previously reported voxel-based GPU ray tracing results. Due to an accelerated simulation time, XDT projections of objects with three spatial dimensions (4D tensor) have also been reported, demonstrating the feasibility for largescale high-dimensional tensor tomography simulations

Bistatic full-wave radar tomography detects deep interior voids, cracks and boulders in a rubble-pile asteroid model

In this paper, we investigate full-wave computed radar tomography (CRT) using a rubble-pile asteroid model in which a realistic shape (Itokawa) is coupled with a synthetic material composition and structure model. The aim is to show that sparse bistatic radar measurements can distinguish details inside a complex-structured rubble-pile asteroid. The results obtained suggest that distinct local permittivity distribution changes such as surface layers, voids, low-permittivity anomalies, high-permittivity boulders, and cracks can be detected with bistatic CRT, when the total noise level in the data is around -10 dB with respect to the signal amplitude. Moreover, the bistatic measurement set-up improves the robustness of the inversion compared to the monostatic case. Reconstructing the smooth Gaussian background distribution was found to be difficult with the present approach, suggesting that complementary techniques, such as gravimetry, might be needed to improve the reliability of the inference in practice.Comment: 15 pages, 7 figures, 3 tables, Published in the Astrophysical Journa