Statistical finite element model for bone shape and biomechanical properties

We present a framework for statistical finite element analysis combining shape and material properties, and allowing performing statistical statements of biomechanical performance across a given population. In this paper, we focus on the design of orthopaedic implants that fit a maximum percentage of the target population, both in terms of geometry and biomechanical stability. CT scans of the bone under consideration are registered non-rigidly to obtain correspondences in position and intensity between them. A statistical model of shape and intensity (bone density) is computed by means of principal component analysis. Afterwards, finite element analysis (FEA) is performed to analyse the biomechanical performance of the bones. Realistic forces are applied on the bones and the resulting displacement and bone stress distribution are calculated. The mechanical behaviour of different PCA bone instances is compared.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

CT radiation dose for computer-assisted endoscopic sinus surgery: dose survey and determination of dose-reduction limits

BACKGROUND AND PURPOSE: Computer-assisted navigation is increasingly used in functional endoscopic sinus surgery (FESS) to prevent injury to vital structures, necessitating preparative CT and, thus, radiation exposure. The purpose of our study was to investigate currently used radiation doses for CT in computer-assisted navigation in sinus surgery (CAS-CT) and to assess minimal doses required. MATERIALS AND METHODS: A questionnaire inquiring about dose parameters used for CAS-CT was sent to 30 radiologic institutions. The feasibility of low-dose registration was tested with a phantom. The influence of CAS-CT dose on technical accuracy and on the practical performance of 5 ear, nose, and throat (ENT) surgeons was evaluated with cadaver heads. RESULTS: The questionnaire response rate was 63%. Variation between minimal and maximal dose used for CAS-CT was 18-fold. Phantom registration was possible with doses as low as 1.1 mGy. No dose dependence on technical accuracy was found. ENT surgeons were able to identify anatomic landmarks on scans with a dose as low as 3.1 mGy. CONCLUSIONS: The vast dose difference between institutions mirrors different attitudes toward image quality and radiation-protection issues rather than being technically founded, and many patients undergo CAS-CT at higher doses than necessary. The only limit for dose reduction in CT for computer-assisted endoscopic sinus surgery is the ENT surgeon's ability to cope with impaired image quality, whereas there is no technically justified lower dose limit. We recommend, generally, doses used for the typical diagnostic low-dose sinus CT (120 kV/20-50 mAs). When no diagnostic image quality is needed, even a reduction down to a third is possible.

"Army of One" to "Army Strong" : visual media and U.S. Army recruitment during Bush"s "War on Terror"

From Bush’s September 20, 2001 “War on Terror” speech to Congress to President-Elect Barack Obama’s acceptance speech on November 4, 2008, the U.S. Army produced visual recruitment material that addressed the concerns of falling enlistment numbers—due to the prolonged and difficult war in Iraq—with quickly-evolving and compelling rhetorical appeals: from the introduction of an “Army of One” (2001) to “Army Strong” (2006); from messages focused on education and individual identity to high-energy adventure and simulated combat scenarios, distributed through everything from printed posters and music videos to first-person tactical-shooter video games. These highly polished, professional visual appeals introduced to the American public during a time of an unpopular war fought by volunteers provide rich subject matter for research and analysis. This dissertation takes a multidisciplinary approach to the visual media utilized as part of the Army’s recruitment efforts during the War on Terror, focusing on American myths—as defined by Barthes—and how these myths are both revealed and reinforced through design across media platforms. Placing each selection in its historical context, this dissertation analyzes how printed materials changed as the War on Terror continued. It examines the television ad that introduced “Army Strong” to the American public, considering how the combination of moving image, text, and music structure the message and the way we receive it. This dissertation also analyzes the video game America’s Army, focusing on how the interaction of the human player and the computer-generated player combine to enhance the persuasive qualities of the recruitment message. Each chapter discusses how the design of the particular medium facilitates engagement/interactivity of the viewer. The conclusion considers what recruitment material produced during this time period suggests about the persuasive strategies of different media and how they create distinct relationships with their spectators. It also addresses how theoretical frameworks and critical concepts used by a variety of disciplines can be combined to analyze recruitment media utilizing a Selber inspired three literacy framework (functional, critical, rhetorical) and how this framework can contribute to the multimodal classroom by allowing instructors and students to do a comparative analysis of multiple forms of visual media with similar content.

Design and implementation of a 3D computer game controller using inertial MEMS sensors

Though 3D computer graphics has seen tremendous advancement in the past two decades, most available mechanisms for computer interaction in 3D are high cost and targeted for industry and virtual reality applications. Recent advances in Micro-Electro-Mechanical-System (MEMS) devices have brought forth a variety of new low-cost, low-power, miniature sensors with high accuracy, which are well suited for hand-held devices. In this work a novel design for a 3D computer game controller using inertial sensors is proposed, and a prototype device based on this design is implemented. The design incorporates MEMS accelerometers and gyroscopes from Analog Devices to measure the three components of the acceleration and angular velocity. From these sensor readings, the position and orientation of the hand-held compartment can be calculated using numerical methods. The implemented prototype is utilizes a USB 2.0 compliant interface for power and communication with the host system. A Microchip dsPIC microcontroller is used in the design. This microcontroller integrates the analog to digital converters, the program memory flash, as well as the core processor, on a single integrated circuit. A PC running Microsoft Windows operating system is used as the host machine. Prototype firmware for the microcontroller is developed and tested to establish the communication between the design and the host, and perform the data acquisition and initial filtering of the sensor data. A PC front-end application with a graphical interface is developed to communicate with the device, and allow real-time visualization of the acquired data.

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

The coevolution of cooperation and dispersal in social groups and its implications for the emergence of multicellularity

Background Recent work on the complexity of life highlights the roles played by evolutionary forces at different levels of individuality. One of the central puzzles in explaining transitions in individuality for entities ranging from complex cells, to multicellular organisms and societies, is how different autonomous units relinquish control over their functions to others in the group. In addition to the necessity of reducing conflict over effecting specialized tasks, differentiating groups must control the exploitation of the commons, or else be out-competed by more fit groups. Results We propose that two forms of conflict – access to resources within groups and representation in germ line – may be resolved in tandem through individual and group-level selective effects. Specifically, we employ an optimization model to show the conditions under which different within-group social behaviors (cooperators producing a public good or cheaters exploiting the public good) may be selected to disperse, thereby not affecting the commons and functioning as germ line. We find that partial or complete dispersal specialization of cheaters is a general outcome. The propensity for cheaters to disperse is highest with intermediate benefit:cost ratios of cooperative acts and with high relatedness. An examination of a range of real biological systems tends to support our theory, although additional study is required to provide robust tests. Conclusion We suggest that trait linkage between dispersal and cheating should be operative regardless of whether groups ever achieve higher levels of individuality, because individual selection will always tend to increase exploitation, and stronger group structure will tend to increase overall cooperation through kin selected benefits. Cheater specialization as dispersers offers simultaneous solutions to the evolution of cooperation in social groups and the origin of specialization of germ and soma in multicellular organisms.

Issues of spectral quality in clinical 1H-magnetic resonance spectroscopy and a gallery of artifacts

In spite of the facts that magnetic resonance spectroscopy (MRS) is applied as clinical tool in non-specialized institutions and that semi-automatic acquisition and processing tools can be used to produce quantitative information from MRS exams without expert information, issues of spectral quality and quality assessment are neglected in the literature of MR spectroscopy. Even worse, there is no consensus among experts on concepts or detailed criteria of quality assessment for MR spectra. Furthermore, artifacts are not at all conspicuous in MRS and can easily be taken for true, interpretable features. This article aims to increase interest in issues of spectral quality and quality assessment, to start a larger debate on generally accepted criteria that spectra must fulfil to be clinically and scientifically acceptable, and to provide a sample gallery of artifacts, which can be used to raise awareness for potential pitfalls in MRS.

The identification of cerebral volume changes in treated growth hormone-deficient adults using serial 3D MR image processing

A pilot study to detect volume changes of cerebral structures in growth hormone (GH)-deficient adults treated with GH using serial 3D MR image processing and to assess need for segmentation prior to registration was conducted.

Knowledge-Production Processes in Practice Research - Outcomes and Critical Elements

The welfare sector has seen considerable changes in its operational context. Welfare services respond to an increasing number of challenges as citizens are confronted with life’s uncertainties and a variety of complex situations. At the same time the service-delivery system is facing problems of co-operation and the development of staff competence, as well as demands to improve service effectiveness and outcomes. In order to ensure optimal user outcomes in this complex, evolving environment it is necessary to enhance professional knowledge and skills, and to increase efforts to develop the services. Changes are also evident in the new emergent knowledge-production models. There has been a shift from knowledge acquisition and transmission to its construction and production. New actors have stepped in and the roles of researchers are subject to critical discussion. Research outcomes, in other words the usefulness of research with respect to practice development, is a topical agenda item. Research is needed, but if it is to be useful it needs to be not only credible but also useful in action. What do we know about different research processes in practice? What conceptions, approaches, methods and actor roles are embedded? What is the effect on practice? How does ‘here and now’ practice challenge research methods? This article is based on the research processes conducted in the institutes of practice research in social work in Finland. It analyses the different approaches applied by elucidating the theoretical standpoints and the critical elements embedded in them, and reflects on the outcomes in and for practice. It highlights the level of change and progression in practice research, arguing for diverse practice research models with a solid theoretical grounding, rigorous research processes, and a supportive infrastructure.

Landscape connectivity, habitat structure and activity of bat guilds in farmland-dominated matrices

Agricultural intensification has caused a decline in structural elements in European farmland, where natural habitats are increasingly fragmented. The loss of habitat structures has a detrimental effect on biodiversity and affects bat species that depend on vegetation structures for foraging and commuting. We investigated the impact of connectivity and configuration of structural landscape elements on flight activity, species richness and diversity of insectivorous bats and distinguished three bat guilds according to species-specific bioacoustic characteristics. We tested whether bats with shorter-range echolocation were more sensitive to habitat fragmentation than bats with longer-range echolocation. We expected to find different connectivity thresholds for the three guilds and hypothesized that bats prefer linear over patchy landscape elements. Bat activity was quantified using repeated acoustic monitoring in 225 locations at 15 study plots distributed across the Swiss Central Plateau, where connectivity and the shape of landscape elements were determined by spatial analysis (GIS). Spectrograms of bat calls were assigned to species with the software batit by means of image recognition and statistical classification algorithms. Bat activity was significantly higher around landscape elements compared to open control areas. Short- and long-range echolocating bats were more active in well-connected landscapes, but optimal connectivity levels differed between the guilds. Species richness increased significantly with connectivity, while species diversity did not (Shannon's diversity index). Total bat activity was unaffected by the shape of landscape elements. Synthesis and applications. This study highlights the importance of connectivity in farmland landscapes for bats, with shorter-range echolocating bats being particularly sensitive to habitat fragmentation. More structurally diverse landscape elements are likely to reduce population declines of bats and could improve conditions for other declining species, including birds. Activity was highest around optimal values of connectivity, which must be evaluated for the different guilds and spatially targeted for a region's habitat configuration. In a multi-species approach, we recommend the reintroduction of structural elements to increase habitat heterogeneity should become part of agri-environment schemes.

Quantification of Popliteal Artery Deformation During Leg Flexion in Subjects With Peripheral Artery Disease: A Pilot Study

Purpose: To quantify the in vivo deformations of the popliteal artery during leg flexion in subjects with clinically relevant peripheral artery disease (PAD). Methods: Five patients (4 men; mean age 69 years, range 56–79) with varying calcification levels of the popliteal artery undergoing endovascular revascularization underwent 3-dimensional (3D) rotational angiography. Image acquisition was performed with the leg straight and with a flexion of 70°/20° in the knee/hip joints. The arterial centerline and the corresponding branches in both positions were segmented to create 3D reconstructions of the arterial trees. Axial deformation, twisting, and curvatures were quantified. Furthermore, the relationships between the calcification levels and the deformations were investigated. Results: An average shortening of 5.9%±2.5% and twist rate of 3.8±2.2°/cm in the popliteal artery were observed. Maximal curvatures in the straight and flexed positions were 0.12±0.04 cm−1 and 0.24±0.09 cm−1, respectively. As the severity of calcification increased, the maximal curvature in the straight position increased from 0.08 to 0.17 cm−1, while an increase from 0.17 to 0.39 cm−1 was observed for the flexed position. Axial elongations and arterial twisting were not affected by the calcification levels. Conclusion: The popliteal artery of patients with symptomatic PAD is exposed to significant deformations during flexion of the knee joint. The severity of calcification directly affects curvature, but not arterial length or twisting angles. This pilot study also showed the ability of rotational angiography to quantify the 3D deformations of the popliteal artery in patients with various levels of calcification.

In vitro accuracy evaluation of image-guided robot system for direct cochlear access

HYPOTHESIS A previously developed image-guided robot system can safely drill a tunnel from the lateral mastoid surface, through the facial recess, to the middle ear, as a viable alternative to conventional mastoidectomy for cochlear electrode insertion. BACKGROUND Direct cochlear access (DCA) provides a minimally invasive tunnel from the lateral surface of the mastoid through the facial recess to the middle ear for cochlear electrode insertion. A safe and effective tunnel drilled through the narrow facial recess requires a highly accurate image-guided surgical system. Previous attempts have relied on patient-specific templates and robotic systems to guide drilling tools. In this study, we report on improvements made to an image-guided surgical robot system developed specifically for this purpose and the resulting accuracy achieved in vitro. MATERIALS AND METHODS The proposed image-guided robotic DCA procedure was carried out bilaterally on 4 whole head cadaver specimens. Specimens were implanted with titanium fiducial markers and imaged with cone-beam CT. A preoperative plan was created using a custom software package wherein relevant anatomical structures of the facial recess were segmented, and a drill trajectory targeting the round window was defined. Patient-to-image registration was performed with the custom robot system to reference the preoperative plan, and the DCA tunnel was drilled in 3 stages with progressively longer drill bits. The position of the drilled tunnel was defined as a line fitted to a point cloud of the segmented tunnel using principle component analysis (PCA function in MatLab). The accuracy of the DCA was then assessed by coregistering preoperative and postoperative image data and measuring the deviation of the drilled tunnel from the plan. The final step of electrode insertion was also performed through the DCA tunnel after manual removal of the promontory through the external auditory canal. RESULTS Drilling error was defined as the lateral deviation of the tool in the plane perpendicular to the drill axis (excluding depth error). Errors of 0.08 ± 0.05 mm and 0.15 ± 0.08 mm were measured on the lateral mastoid surface and at the target on the round window, respectively (n =8). Full electrode insertion was possible for 7 cases. In 1 case, the electrode was partially inserted with 1 contact pair external to the cochlea. CONCLUSION The purpose-built robot system was able to perform a safe and reliable DCA for cochlear implantation. The workflow implemented in this study mimics the envisioned clinical procedure showing the feasibility of future clinical implementation.

Fully automatic X-ray image segmentation via joint estimation of image displacements.

We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.