Correlation modeling for compression of computed tomography images

Abstract-Computed Tomography (CT) is a noninvasive medical test obtained via a series of X-ray exposures resulting in 3D images that aid medical diagnosis. Previous approaches for coding such 3D images propose to employ multi-component transforms to exploit correlation among CT slices, but these approaches do not always improve coding performance with respect to a simpler slice-by-slice coding approach. In this work, we propose a novel analysis which accurately predicts when the use of a multi-component transform is profitable. This analysis models the correlation coefficient r based on image acquisition parameters readily available at acquisition time. Extensive experimental results from multiple image sensors suggest that multi-component transforms are appropriate for images with correlation coefficient r in excess of 0.87

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes

Determination of local material properties of OSB sample by coupling advanced imaging techniques and morphology-based FEM simulation

This is the publisher’s final pdf. The published article is copyrighted by Walter de Gruyter & Co. and can be found at: http://www.degruyter.com/.The goal was to determine local mechanical properties inside of oriented strand board (OSB) based on a realistic morphology-based finite element (FE) model and data acquired from a physical test performed on the same material. The spatial information and local grayscale intensity from CT-scans obtained from small OSB sample was transformed into a 2D regular morphology-based FE mesh with corresponding material properties. The model was then used to simulate the actual compression test performed on the specimen using simplified boundary conditions. The simulated strain fields from the model were compared with the actual strain field measured on the specimen surface during the compression test by means of a full-field optical method, named digital image correlation (DIC). Finally, the original set of material properties was adjusted by an iterative procedure to minimize the difference between the simulated and the measured strain data. The results show that the developed procedure is useful to find local material properties as well as for morphological modeling without the need of segmentation of the image data. The achieved results serve as a prerequisite for full 3D analyses of the complex materials

In-situ Analysis of Laminated Composite Materials by X-ray Micro-Computed Tomography and Digital Volume Correlation

The complex mechanical behaviour of composite materials, due to internal heterogeneity and multi-layered composition impose deeper studies. This paper presents an experimental investigation technique to perform volume kinematic measurements in composite materials. The association of X-ray micro-computed tomography acquisitions and Digital Volume Correlation (DVC) technique allows the measurement of displacements and deformations in the whole volume of composite specimen. To elaborate the latter, composite fibres and epoxy resin are associated with metallic particles to create contrast during X-ray acquisition. A specific in situ loading device is presented for three-point bending tests, which enables the visualization of transverse shear effects in composite structures

Modelling and characterization of cell collapse in aluminium foams during dynamic loading

Plate-impact experiments have been conducted to investigate the elastic–plastic behaviour of shock wave propagation and pore collapse mechanisms of closed-cell aluminium foams. FE modelling using a meso-scale approach has been carried out with the FE software ABAQUS/Explicit. A micro-computed tomography-based foam geometry has been developed and microstructural changes with time have been investigated to explore the effects of wave propagation. Special attention has been given to the pore collapse mechanism. The effect of velocity variations on deformation has been elucidated with three different impact conditions using the plate-impact method. Free surface velocity (ufs) was measured on the rear of the sample to understand the evolution of the compaction. At low impact velocities, the free-surface velocity increased gradually, whereas an abrupt rise of free-surface velocity was found at an impact velocity of 845 m/s with a copper flyer-plate which correlates with the appearance of shock. A good correlation was found between experimental results and FE predictions

Medical imaging analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging

Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets

The density, porosity, breaking force, viscoelastic properties, and the presence or absence of any structural defects or irregularities are important physical-mechanical quality attributes of popular solid dosage forms like tablets. The irregularities associated with these attributes may influence the drug product functionality. Thus, an accurate and efficient characterization of these properties is critical for successful development and manufacturing of a robust tablets. These properties are mainly analyzed and monitored with traditional pharmacopeial and non-pharmacopeial methods. Such methods are associated with several challenges such as lack of spatial resolution, efficiency, or sample-sparing attributes. Recent advances in technology, design, instrumentation, and software have led to the emergence of newer techniques for non-invasive characterization of physical-mechanical properties of tablets. These techniques include near infrared spectroscopy, Raman spectroscopy, X-ray microtomography, nuclear magnetic resonance (NMR) imaging, terahertz pulsed imaging, laser-induced breakdown spectroscopy, and various acoustic- and thermal-based techniques. Such state-of-the-art techniques are currently applied at various stages of development and manufacturing of tablets at industrial scale. Each technique has specific advantages or challenges with respect to operational efficiency and cost, compared to traditional analytical methods. Currently, most of these techniques are used as secondary analytical tools to support the traditional methods in characterizing or monitoring tablet quality attributes. Therefore, further development in the instrumentation and software, and studies on the applications are necessary for their adoption in routine analysis and monitoring of tablet physical-mechanical properties