Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

Objective

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

Materials and methods

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader’s subjective confidence to assess the images (not confident, confident, very confident).

Results

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as ‘perfusion deficit’, 113 vs. 109 as ‘dark rim artifacts’, 9 vs. 7 as ‘uncertain signal loss’, and 817 vs. 824 as ‘normal’. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as ‘good’ or ‘excellent’ (92 vs. 63%), and the diagnostic confidence more often as “very confident” (71 vs. 45%) compared to non-MoCo.

Conclusions

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader’s subjective confidence to assess the images were rated more favorably for MoCo.

     

Innovative User Interfaces in Automation Engineering by Application of Usability Engineering Methods Shown by the Example of a Three-Dimensional Plant Representation

This article is the first of 3 that focus on user-centered design and usability in the field of industrial process control. This article starts with an introduction to this special domain and sets out the need for user-centered design of innovative user interfaces. The MediaPlant research project is then introduced. This project aims to generate innovative user interface solutions for process control. The usability engineering methods presented are well known in relation to office application software and were applied in the course of the project to (a) evaluate the potential and application fields of innovative multimedia technology and 3-dimensional information presentation (described at the end of this article), (b) define innovative user interface building blocks for process control that can be applied across sectors (described in the second article, Komischke & Burmester [this issue]) and (c) develop human-centered user interfaces for controlling paper recycling plants (described in the third article, Epstein & Beu [this issue]).     

Spatial inverse query processing

Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches.     

A benchmark of kriging-based infill criteria for noisy optimization

Responses of many real-world problems can only be evaluated perturbed by noise. In order to make an efficient optimization of these problems possible, intelligent optimization strategies successfully coping with noisy evaluations are required. In this article, a comprehensive review of existing kriging-based methods for the optimization of noisy functions is provided. In summary, ten methods for choosing the sequential samples are described using a unified formalism. They are compared on analytical benchmark problems, whereby the usual assumption of homoscedastic Gaussian noise made in the underlying models is meet. Different problem configurations (noise level, maximum number of observations, initial number of observations) and setups (covariance functions, budget, initial sample size) are considered. It is found that the choices of the initial sample size and the covariance function are not critical. The choice of the method, however, can result in significant differences in the performance. In particular, the three most intuitive criteria are found as poor alternatives. Although no criterion is found consistently more efficient than the others, two specialized methods appear more robust on average.     

Development of a coupled land-atmosphere satellite data assimilation system for improved local atmospheric simulations

This study developed a coupled land-atmosphere satellite data assimilation system as a new physical downscaling approach, by coupling a mesoscale atmospheric model with a land data assimilation system (LDAS). The LDAS consists of a land surface scheme as the model operator, a radiative transfer model as the observation operator, and the simulated annealing method for minimizing the difference between the observed and simulated microwave brightness temperature. The atmospheric model produces forcing data for the LDAS, and the LDAS produces better initial surface conditions for the modelling system. This coupled system can take into account land surface heterogeneities through assimilating satellite data for a better precipitation prediction. To assess the effectiveness of the new system, 3-dimensional numerical experiments were carried out in a mesoscale area of the Tibetan Plateau during the wet monsoon season. The results show significant improvement compared with a no assimilation regional atmospheric model simply nested from the global model. The surface soil moisture content and its distribution from the assimilation system were more consistent to in situ observations. These better surface conditions affect the land-atmosphere interactions through convection systems and lead to better atmospheric predictability as confirmed by satellite-based cloud observations and in situ sounding observations. Through the use of satellite brightness temperature, the developed coupled land-atmosphere assimilation system has shown potential ability to provide better initial surface conditions and its inputs to the atmosphere and to improve physical downscaling through regional models.     

Decentralised control of chromatographic simulated moving bed processes based on wave front reconstruction

The behaviour of chromatographic simulated moving bed processes is described by the movement of concentration profiles through a circle of separation columns. A closed-loop control manipulates the profiles in order to meet demands concerning specified product purity and disturbance attenuation. If steep wave fronts of the concentration profiles occur, the controlled variables undergo fast changes in case of a transient of the process. In this case, a reconstruction of the wave fronts is necessary for a successful control.A simple and effective decentralised controller structure is proposed based on cascaded discrete-time PI controllers. On-line product purity measurements and the reconstructed wave fronts are used for control purposes. Two kinds of process models are used: a rigorous model for dynamic simulations, and strongly simplified plant models for the design of the wave front reconstruction and the controller. The latter models are identified based on experimental step tests with the reference plant and numerical simulations. The performance of the control system is evaluated by numerical simulations.     

Depth-Fused 3D Imagery on an Immaterial Display

We present an immaterial display that uses a generalized form of depth-fused 3D (DFD) rendering to create unencumbered 3D visuals. To accomplish this result, we demonstrate a DFD display simulator that extends the established depth-fused 3D principle by using screens in arbitrary configurations and from arbitrary viewpoints. The feasibility of the generalized DFD effect is established with a user study using the simulator. Based on these results, we developed a prototype display using one or two immaterial screens to create an unencumbered 3D visual that users can penetrate, examining the potential for direct walk-through and reach-through manipulation of the 3D scene. We evaluate the prototype system in formative and summative user studies and report the tolerance thresholds discovered for both tracking and projector errors.     

Multithreaded Hybrid Feature Tracking for Markerless Augmented Reality

We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.     

An artist life cycle model for digital media content: Strategies for the Light Web and the Dark Web

This paper surveys and categorizes emerging digital media business models. We apply the customer activity cycle of Vandermerwe (2000) to the consumption of digital media, taking three phases into account: pre-consumption, consumption and post-consumption. Our analysis of the business models focuses on their social costs and benefits. We derive the parameters as follows: convenience of use, exposure, ease of compliance and administration. We distinguish two polar environments for digital media: the Dark Web with content created by the masses, and the Light Web with content created by big media. We develop an artist life cycle model in which different business models appear to be optimal at different stages of an artist’s career. Voluntary payment-based models seem to be ideal for newcomers in the Dark Web, while digital rights management-based and complementary product and service-based models are the likely choice of established artists in the Light Web. Established artists might change their approach again, using voluntary payment-based or complementary product and service-based models when they retire.     

An Interoperable Grid Information System for Integrated Resource Monitoring Based on Virtual Organizations

In many Grid infrastructures different kinds of information services are in use, which utilize different incompatible data structures and interfaces to encode and provide their data. Homogeneous monitoring of these infrastructures with the monitoring data being accessible everywhere independently of the middleware which provided it, is the basis for a consistent status reporting on the Grids’ resources and services. Thus, interoperability or interoperation between the different information services in a heterogeneous Grid infrastructure is required. Monitoring data must contain the identity of the affected Virtual Organization (VO) so that it can be related to the resources and services the VO has allocated to enable VO-specific information provision. This paper describes a distributed architecture for an interoperable information service, which combines data unification and categorization with policies for VO membership, VO resource management and data transformations. This service builds the basis for an integrated and interoperating monitoring of Grids, which provide their data to more than one VO and utilize heterogeneous information services.