Three-Dimensional Reconstruction Algorithm for a Reverse-Geometry Volumetric CT System With a Large-Array Scanned Source

We have proposed a CT system design to rapidly produce volumetric images with negligible cone beam artifacts. The investigated system uses a large array scanned source with a smaller array of fast detectors. The x-ray source is electronically steered across a 2D target every few milliseconds as the system rotates. The proposed reconstruction algorithm for this system is a modified 3D filtered backprojection method. The data are rebinned into 2D parallel ray projections, most of which are tilted with respect to the axis of rotation. Each projection is filtered with a 2D kernel and backprojected onto the desired image matrix. To ensure adequate spatial resolution and low artifact level, we rebin the data onto an array that has sufficiently fine spatial and angular sampling. Due to finite sampling in the real system, some of the rebinned projections will be sparse, but we hypothesize that the large number of views will compensate for the data missing in a particular view. Preliminary results using simulated data with the expected discrete sampling of the source and detector arrays suggest that high resolution

Noise Simulations For an Inverse-Geometry Volumetric CT System

This paper examines the noise performance of an inverse-geometry volumetric CT (IGCT) scanner through simulations. The IGCT system uses a large area scanned source and a smaller array of detectors to rapidly acquire volumetric data with negligible cone-beam artifacts. The first investigation compares the photon efficiency of the IGCT geometry to a 2D parallel ray system. The second investigation models the photon output of the IGCT source and calculates the expected noise. For the photon efficiency investigation. the same total number of photons was modeled in an IGCT acquisition and a comparable multi-slice 2D parallel ray acquisition. For both cases noise projections were simulated and the central axial slice reconstructed. In the second study. to investigate the noise in an IGCT system, the expected x-ray photon flux was modeled and projections simulated through ellipsoid phantoms. All simulations were compared to theoretical predictions. The results of the photon efficiency simulations verify that the IGCT geometry is as efficient in photon utilization as a 2D parallel ray geometry. For a 10 cm diameter 4 cm thick ellipsoid water phantom and for reasonable system parameters, the calculated standard deviation was approximately 15 HU at the center of the ellipsoid. For the same size phantom with maximum attenuation equivalent to 30 cm of water, the calculated noise was approximately 131 HU. The theoretical noise predictions for these objects were 15 HU and 112 HU respectively. These results predict acceptable noise levels for a system with a 0.16 second scan time and 12 lp/cm isotropic resolution

Tenfold your photons -- a physically-sound approach to filtering-based variance reduction of Monte-Carlo-simulated dose distributions

X-ray dose constantly gains interest in the interventional suite. With dose being generally difficult to monitor reliably, fast computational methods are desirable. A major drawback of the gold standard based on Monte Carlo (MC) methods is its computational complexity. Besides common variance reduction techniques, filter approaches are often applied to achieve conclusive results within a fraction of time. Inspired by these methods, we propose a novel approach. We down-sample the target volume based on the fraction of mass, simulate the imaging situation, and then revert the down-sampling. To this end, the dose is weighted by the mass energy absorption, up-sampled, and distributed using a guided filter. Eventually, the weighting is inverted resulting in accurate high resolution dose distributions. The approach has the potential to considerably speed-up MC simulations since less photons and boundary checks are necessary. First experiments substantiate these assumptions. We achieve a median accuracy of 96.7 % to 97.4 % of the dose estimation with the proposed method and a down-sampling factor of 8 and 4, respectively. While maintaining a high accuracy, the proposed method provides for a tenfold speed-up. The overall findings suggest the conclusion that the proposed method has the potential to allow for further efficiency.Comment: 6 pages, 3 figures, Bildverarbeitung f\"ur die Medizin 202

Precision Learning: Towards Use of Known Operators in Neural Networks

In this paper, we consider the use of prior knowledge within neural networks. In particular, we investigate the effect of a known transform within the mapping from input data space to the output domain. We demonstrate that use of known transforms is able to change maximal error bounds. In order to explore the effect further, we consider the problem of X-ray material decomposition as an example to incorporate additional prior knowledge. We demonstrate that inclusion of a non-linear function known from the physical properties of the system is able to reduce prediction errors therewith improving prediction quality from SSIM values of 0.54 to 0.88. This approach is applicable to a wide set of applications in physics and signal processing that provide prior knowledge on such transforms. Also maximal error estimation and network understanding could be facilitated within the context of precision learning.Comment: accepted on ICPR 201

Geometry Analysis of an Inverse-Geometry Volumetric CT System With Multiple Detector Arrays

An inverse-geometry volumetric CT (IGCT) system for imaging in a single fast rotation without cone-beam artifacts is being developed. It employs a large scanned source array and a smaller detector array. For a single-source/single-detector implementation, the FOV is limited to a fraction of the source size. Here we explore options to increase the FOV without increasing the source size by using multiple detectors spaced apart laterally to increase the range of radial distances sampled. We also look at multiple source array systems for faster scans. To properly reconstruct the FOV, Radon space must be sufficiently covered and sampled in a uniform manner. Optimal placement of the detectors relative to the source was determined analytically given system constraints (5cm detector width, 25cm source width, 45cm source-to-isocenter distance). For a 1x3 system (three detectors per source) detector spacing (DS) was 18deg and source-to-detector distances (SDD) were 113, 100 and 113cm to provide optimum Radon sampling and a FOV of 44cm. For multiple-source systems, maximum angular spacing between sources cannot exceed 125deg since detectors corresponding to one source cannot be occluded by a second source. Therefore, for 2x3 and 3x3 systems using the above DS and SDD, optimum spacing between sources is 115deg and 61deg respectively, requiring minimum scan rotations of 115deg and 107deg. Also, a 3x3 system can be much faster for full 360deg dataset scans than a 2x3 system (120deg vs. 245deg). We found that a significantly increased FOV can be achieved while maintaining uniform radial sampling as well as a substantial reduction in scan time using several different geometries. Further multi-parameter optimization is underway

A Product Model based Approach to Interactive CAE Design Optimization

We present a software prototype for fluid flow problems in civil engineering, which combines essential features of Computational Steering approaches with efficient methods for model transfer and high performance computing. The main components of the system are described: - The modeler with a focus on the data management of the product model - The pre-processing and the post-processing toolkit - The simulation kernel based on the Lattice Boltzmann method - The required hardware for real-time computin

Lessons from integrating behaviour and resource selection: activity-specific responses of African wild dogs to roads

Understanding how anthropogenic features affect species' abilities to move within landscapes is essential to conservation planning and requires accurate assessment of resource selection for movement by focal species. Yet, the extent to which an individual's behavioural state (e.g. foraging, resting, commuting) influences resource selection has largely been ignored. Recent advances in Global Positioning System (GPS) tracking technology can fill this gap by associating distinct behavioural states with location data. We investigated the role of behaviour in determining the responses of an endangered species of carnivore, the African wild dog Lycaon pictus, to one of the most widespread forms of landscape alteration globally: road systems. We collected high‐resolution GPS and activity data from 13 wild dogs in northern Botswana over a 2‐year period. We employed a step selection framework to measure resource selection across three behavioural states identified from activity data (high‐speed running, resting and travelling) and across a gradient of habitats and seasons, and compared these outputs to a full model that did not parse for behaviour. The response of wild dogs to roads varied markedly with both the behavioural and the landscape contexts in which roads were encountered. Specifically, wild dogs selected roads when travelling, ignored roads when high‐speed running and avoided roads when resting. This distinction was not evident when all movement data were considered together in the full model. When travelling, selection for roads increased in denser vegetative environments, suggesting that roads may enhance movement for this species. Our findings indicate that including behavioural information in resource selection models is critical to understanding wildlife responses to landscape features and suggest that successful application of resource selection analyses to conservation planning requires explicit examination of the behavioural contexts in which movement occurs. Thus, behaviour‐specific step selection functions offer a powerful tool for identifying resource selection patterns for animal behaviours of conservation significance

The legacy of 20th Century landscape change on today’s woodland carabid communities

Aim For many species, the effects of landscape change can involve a time lag and result in an extinction debt. The landscape matrix plays a vital role in supporting species populations. However, the importance of the historical composition and configuration of landscape mosaics has received little attention, with studies focusing on the effects of loss and fragmentation of single (focal) habitat over time. We investigated the importance of historical and contemporary landscape heterogeneity (composition and configuration) to identify how landscape change has, and is continuing to have, an effect on current woodland carabid communities. Location Lowland Britain. Methods Carabids were sampled from woodlands in 36 tetrads of 4 km2. Ordination methods analysed current community response to representations of contemporary and historical (1930’s) landscape heterogeneity. The effects of 80 years of landscape change on current carabid assemblages were compared among tetrads. Results Results are consistent with an extinction debt; carabid communities correlated significantly with the historical composition and configuration of the landscape, but not contemporary landscape configuration. Community assemblages have been shaped, and many species remain affiliated with landscape conditions that no longer exist, notably, large patches of broadleaf woodland and semi-natural grassland. Recent introduction of conifer plantations has had a negative effect on the abundance of many woodland species. For many common, slow-dispersing species, contemporary and historical landscapes offered sub-optimum woodland coverage indicating a lag effect that exceeds 80 years. Increased arable landcover and loss of semi-natural grassland and heathland points towards an ongoing detrimental impact on carabid populations. Main conclusions Compared with focal-habitat studies, the landscape mosaic approach provides a more comprehensive understanding of the effects of widespread landscape change on species communities. Conservation guidance includes new planting, maintenance and restoration of semi-natural habitats, implemented across multiple spatial scales and where feasible, considering both historical and contemporary landscape heterogeneity