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

Clinical indications for digital imaging in dento-alveolar trauma. Part 1: traumatic injuries

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73819/1/j.1600-9657.2006.00509.x.pd

TORT3D: A MATLAB code to compute geometric tortuosity from 3D images of unconsolidated porous media

Tortuosity is a parameter that plays a significant role in the characterization of complex porous media systems and it has a significant impact on many engineering and environmental processes and applications. Flow in porous media, diffusion of gases in complex pore structures and membrane flux in water desalination are examples of the application of this important micro-scale parameter. In this paper, an algorithm was developed and implemented as a MATLAB code to compute tortuosity from three-dimensional images. The code reads a segmented image and finds all possible tortuous paths required to compute tortuosity. The code is user-friendly, easy to use and computationally efficient, as it requires a relatively short time to identify all possible connected paths between two boundaries of large images. The main idea of the developed algorithm is that it conducts a guided search for connected paths in the void space of the image utilizing the medial surface of the void space. Once all connected paths are identified in a specific direction, the average of all connected paths in that direction is used to compute tortuosity. Three-dimensional images of sand systems acquired using X-ray computed tomography were used to validate the algorithm. Tortuosity values were computed from three-dimensional images of nine different natural sand systems using the developed algorithm and compared with predicted values by models available in the literature. Findings indicate that the code can successfully compute tortuosity for any unconsolidated porous system irrespective of the shape (i.e., geometry) of particles. 1 2017 Elsevier B.V.Scopu

An Automatic Regularization Method : An Application for 3-D X-Ray Micro-CT Reconstruction Using Sparse Data

X-ray tomography is a reliable tool for determining the inner structure of 3-D object with penetrating X-rays. However, traditional reconstruction methods, such as Feldkamp-Davis-Kress (FDK), require dense angular sampling in the data acquisition phase leading to long measurement times, especially in X-ray micro-tomography to obtain high-resolution scans. Acquiring less data using greater angular steps is an obvious way for speeding up the process and avoiding the need to save huge data sets. However, computing 3-D reconstruction from such a sparsely sampled data set is difficult because the measurement data are usually contaminated by errors, and linear measurement models do not contain sufficient information to solve the problem in practice. An automatic regularization method is proposed for robust reconstruction, based on enforcing sparsity in the 3-D shearlet transform domain. The inputs of the algorithm are the projection data and a priori known expected degree of sparsity, denoted as 0 <C-prPeer reviewe

An Overview of the Measurement of Permeability of Composite Reinforcements

Liquid composite molding (LCM) is a class of fast and cheap processes suitable for the fabrication of large parts with good geometrical and mechanical properties. One of the main steps in an LCM process is represented by the filling stage, during which a reinforcing fiber preform is impregnated with a low-viscosity resin. Darcy’s permeability is the key property for the filling stage, not usually available and depending on several factors. Permeability is also essential in computational modeling to reduce costly trial-and-error procedures during composite manufacturing. This review aims to present the most used and recent methods for permeability measurement. Several solutions, introduced to monitor resin flow within the preform and to calculate the in-plane and out-of-plane permeability, will be presented. Finally, the new trends toward reliable methods based mainly on non-invasive and possibly integrated sensors will be described

Explosive Detection Equipment and Technology for Border Security

This report contains a brief survey of Explosives Detection Technology,as it is applied for inspection of goods and passengers at borders, and explains the role of European legislation and the European Commission¿s research programs in this field. It describes the techniques of trace and bulk explosives detection that are in use, the latest techniques that are in development and the characteristics of explosives that are, or might be, used to provide a signature for exploitation in detection technology. References to academic reviews are included for those wishing to study the subject in greater depth. Some additional details are given concerning plastic and liquid explosives, which are a threat of particular current importance. The report also contains a brief account of relevant European trade, safety and security legislation, a description of recent policy initiatives and tables of related European Commission funded research projects. Contact details of commercial companies selling explosive detection products are also provided.JRC.G.6-Sensors, radar technologies and cybersecurit

In vitro detection of mesio-buccal canals in maxillary molar cross-sections using three different resolutions with Kodak 9000 3D CBCT.

CBCT in endodontics demonstrates anatomic features in 3D that intraoral, panoramic, and cephalometric images cannot. CBCT units reconstruct the projection data to provide interrelational images in three orthogonal planes (axial, sagittal, and coronal). In addition because reconstruction of CBCT data is performed natively using a personal computer, data can be reoriented in their true spatial relationships. Aims: To investigate accurate detection of the correct number of root canals in the mesio-buccal root of the maxillary molar teeth using 3D imaging with cone beam computed tomography (CBCT) at different spatial resolution (isotropic voxel) settings. Methods: With IRB approval, 31 extracted maxillary molars were examined using high resolution, small field of view CBCT at isotropic voxel resolutions ranging at 0.076, 0.10 and 0.20 mm. The image data sets were imported into third party segmentation software to provide 3D videos for 8 observers to determine the number of mesio-buccal root canals in cross-sectional reconstructions. The ground truth was later established by sectioning the tooth roots axially. Results: Twenty-four of the teeth proved on sectioning to have two mesio-buccal canals whereas the others had one canal. Accuracy in detection of mesio-buccal canals varied between observers from 59% to 75% and statistically unrelated to observer experience. No statistical differences were found between the reconstructed 3D images regarding accurate detection of canals. Conclusions: CBCT outperformed the findings for accuracy in detection of mesio-buccal root canals in all previous studies using 2D imaging modalities and Tuned Aperture Computed Tomography. Keywords: Computed Tomography, X-ray, Cone-Beam; Endodontics; Image processing

Limited view X-ray tomography for dimensional measurements

The growing use of complex and irregularly shaped components for safety-critical applications has increasingly led to the adoption of X-ray CT as an NDE inspection tool. Standard X-ray CT methods require thousands of projections, each regularly distributed evenly through 360∘ to produce an accurate image. The time consuming acquisition of thousands of projections can lead to significant bottlenecks. Recent developments in medical imaging driven by both increasing computational power and the desire to reduce patient X-ray exposure have led to the development of a number of limited view CT methodologies. Thus far these limited view algorithms have been applied to basic synthetic data derived from simple medical phantoms. Here, we use experimental data to rigorously test the capability of limited view algorithms to accurately reconstruct and precisely measure the dimensional features of an additive manufactured sample and a turbine blade. Our findings highlight the importance of prior information in producing accurate reconstructions capable of significantly reducing X-ray projections by at least an order of magnitude. In the turbine blade example a dramatic reduction in projections from 5000 to 24 was observed while still demonstrating the same level of accuracy as standard CT methods. The findings of the study also suggest the importance of sample complexity and the presence of sparsity in the X-ray projections in order to maximise the capabilities of these limited algorithms. With the ever increasing computational power limited view CT algorithms offer a method for reducing data acquisition time and alleviating manufacturing throughput bottlenecks without compromising image accuracy and quality

Mathematics and Algorithms in Tomography

This was the ninth Oberwolfach conference on the mathematics of tomography. Modalities represented at the workshop included X-ray tomography, radar, seismic imaging, ultrasound, electron microscopy, impedance imaging, photoacoustic tomography, elastography, emission tomography, X-ray CT, and vector tomography along with a wide range of mathematical analysis