Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Quantitative PET image reconstruction employing nested expectation-maximization deconvolution for motion compensation

Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources. The proposed algorithms can support compensation for any periodic and non-periodic motion, such as cardio-respiratory or bulk motion, the latter including rolling, twisting or drifting. Inspired from the widely adopted point-spread function (PSF) deconvolution 3D PET reconstruction techniques, here we introduce an image-based 3D generalized motion deconvolution method within the standard 3D maximum-likelihood expectation-maximization (ML-EM) reconstruction framework. In particular, we initially integrate a motion blurring kernel, accounting for every tracked motion within a frame, as an additional MLEM modeling component in the image space (integrated 3D-MCIR). Subsequently, we replaced the integrated model component with a nested iterative Richardson-Lucy (RL) image-based deconvolution method to accelerate the MLEM algorithm convergence rate (RL-3D-MCIR). The final method was evaluated with realistic simulations of whole-body dynamic PET data employing the XCAT phantom and real human bulk motion profiles, the latter estimated from volunteer dynamic MRI scans. In addition, metabolic uptake rate Ki parametric images were generated with the standard Patlak method. Our results demonstrate significant improvement in contrast-to-noise ratio (CNR) and noise-bias performance in both dynamic and parametric images. The proposed nested RL-3D-MCIR method is implemented on the Software for Tomographic Image Reconstruction (STIR) open-source platform and is scheduled for public release

Monitoring 3D vibrations in structures using high resolution blurred imagery

This thesis describes the development of a measurement system for monitoring dynamic tests of civil engineering structures using long exposure motion blurred images, named LEMBI monitoring. Photogrammetry has in the past been used to monitor the static properties of laboratory samples and full-scale structures using multiple image sensors. Detecting vibrations during dynamic structural tests conventionally depends on high-speed cameras, often resulting in lower image resolutions and reduced accuracy. To overcome this limitation, the novel and radically different approach presented in this thesis has been established to take measurements from blurred images in long-exposure photos. The motion of the structure is captured in an individual motion-blurred image, alleviating the dependence on imaging speed. A bespoke algorithm is devised to determine the motion amplitude and direction of each measurement point. Utilising photogrammetric techniques, a model structure s motion with respect to different excitations is captured and its vibration envelope recreated in 3D, using the methodology developed in this thesis. The approach is tested and used to identify changes in the model s vibration response, which in turn can be related to the presence of damage or any other structural modification. The approach is also demonstrated by recording the vibration envelope of larger case studies in 2D, which includes a full-scale bridge structure, confirming the relevance of the proposed measurement approach to real civil engineering case studies. This thesis then assesses the accuracy of the measurement approach in controlled motion tests. Considerations in the design of a survey using the LEMBI approach are discussed and limitations are described. The implications of the newly developed monitoring approach to structural testing are reviewed

Advanced light-sheet and structured illumination microscopy techniques for neuroscience and disease diagnosis

Optical microscopy is a cornerstone of biomedical research. Advances in optical techniques enable specific, high resolution, sterile, and biologically compatible imaging. In particular, beam shaping has been used to tailor microscopy techniques to enhance microscope performance. The aim of this Thesis is to investigate the use of novel beam shaping techniques in emerging optical microscopy methods, and to apply these methods in biomedicine. To overcome the challenges associated with high resolution imaging of large specimens, the use of Airy beams and related techniques are applied to light-sheet microscopy. This approach increases the field-of-view that can be imaged at high resolution by over an order of magnitude compared to standard Gaussian beam based light-sheet microscopy, has reduced phototoxicity, and can be implemented with a low-cost optical system. Advanced implementations show promise for imaging at depth within turbid tissue, in particular for neuroscience. Super-resolution microscopy techniques enhance the spatial resolution of optical methods. Structured illumination microscopy is investigated as an alternative for electron microscopy in disease diagnosis, capable of visualising pathologically relevant features of kidney disease. Separately, compact optical manipulation methods are developed with the aim of adding functionality to super-resolution techniques

IMPROVING THE SPEED AND OPTICAL SECTIONING OF FLUORESCENCE MICROSCOPY TECHNIQUES FOR BIOPHYSICAL ANALYSIS OF SUBCELLULAR PROCESSES

This dissertation focuses on novel fluorescence microscopy techniques and the biophysical analysis of cell biology enabled by such techniques. Modern cell biology research benefits greatly from the ability to accurately visualize the inner workings of cells. Fluorescence microscopy is particularly well suited to imaging live cells, as it is gentle enough to avoid damaging cells, provides sufficient spatial resolution to image small cellular features, and targets and visualizes specific cell structures and processes with high contrast. An additional feature that is often desirable in fluorescence microscopy is the ability to image rapidly enough to freeze the motion of dynamic cell processes, yet technical limitations make imaging with both high spatial and temporal resolution challenging. In this thesis I address methods for improving the speed, spatial resolution, and optical sectioning of fluorescence microscopy techniques. I then apply some of these innovations to study actin structures and dynamics in epithelial cells. Because of its role in driving cellular motion, targeted studies of the actin cytoskeleton using fluorescence microscopy can be used to examine cell migration dynamics. In both in vivo and in vitro experiments, I use high spatiotemporal resolution fluorescence microscopy techniques to provide insight into the role of the actin cytoskeleton in responding to external structural stimuli

Precision measurements with SMI and 4PiMicroscopy

Newly developed farfield light microscopy techniques such as Spatially Modulated Illumination and 4Pi microscopy allow structural measurements on biological objects with a precision very much better than the conventional imaging resolution. This thesis focuses on the improvement of this measurement accuracy, encompassing both changes to the experimental SMI setup and new data analysis procedures. An aberration resistant fit algorithm for SMI microscopy is presented along with similar model based procedures for the analysis of 4Pi and confocal data. These are combined in a framework which allows for robust automatic analysis. A method for deconvolving 4Pi data which shows a refractive index mismatch induced phase shift is also introduced. The devices and the associated algorithms were applied to various biological problems most notably the size of replication foci and the structure of the inner kinetochore. Virtual microscopy simulations were performed to support the interpretation of this data and to obtain insight into the results of the SMI gene structure measurements performed by other group members

Principles and applications of wavefront coding

Abstract unavailable please refer to PD