21 resultados para Autoregressive-Moving Average model
Resumo:
For the development and evaluation of cardiac magnetic resonance (MR) imaging sequences and methodologies, the availability of a periodically moving phantom to model respiratory and cardiac motion would be of substantial benefit. Given the specific physical boundary conditions in an MR environment, the choice of materials and power source of such phantoms is heavily restricted. Sophisticated commercial solutions are available; however, they are often relatively costly and user-specific modifications may not easily be implemented. We therefore sought to construct a low-cost MR-compatible motion phantom that could be easily reproduced and had design flexibility. A commercially available K'NEX construction set (Hyper Space Training Tower, K'NEX Industries, Inc., Hatfield, PA) was used to construct a periodically moving phantom head. The phantom head performs a translation with a superimposed rotation, driven by a motor over a 2-m rigid rod. To synchronize the MR data acquisition with phantom motion (without introducing radiofrequency-related image artifacts), a fiberoptic control unit generates periodic trigger pulses synchronized to the phantom motion. Total material costs of the phantom are US$ < 200.00, and a total of 80 man-hours were required to design and construct the original phantom. With schematics of the present solution, the phantom reproduction may be achieved in approximately 15 man-hours. The presented MR-compatible periodically moving phantom can easily be reproduced, and user-specific modifications may be implemented. Such an approach allows a detailed investigation of motion-related phenomena in MR images.
Resumo:
Background: The 1st Swiss federal Transplant Law was finally enforced in July 2007 with the obligation to promote quality and efficiency in transplant procedures. The LODP was created to develop organ and tissue donation in the Latin area of Switzerland covering seventeen hospitals (29% of the population).Methods: Each of the partner hospitals designated at least one Local Donor Coordinator (LDC), member of the Intensive Care team, trained in the organ donation (OD) process. The principal tasks of the LDC's are the introduction of OD procedures, organisation of educational sessions for hospital staff and execution of the Donor Action programme. The LODP has been operational since July 2009, when training of the LDC's was completed, the web-site and hotline activated and the attendance of Transplant Procurement Coordinators (TPC) during the OD process organised.Results: National and regional guidelines are accessible on the LODP website. The Hospital Attitude Survey obtained a 57% return rate. Many of the staff requested training and sessions are now running in the partner hospitals. The Medical Record Revue revealed an increase in the conversion rate from 3.5% to 4.5%. During the 5 years before creation of LODP the average annual number of utilised donors was 31, an increase of 70%, has since been observed.Conclusion: This clear progression in utilised donors in the past two years can be attributed to the fact that partner hospitals benefit from the various support given (hotline, website and from TPC's). Despite the increase in OD within the LODP the Swiss donation rates remain low, on average 11.9 donors per million population. This successful model should be applied throughout Switzerland, but the crucial point is to obtain financial support.
Resumo:
PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.
Resumo:
Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.
Resumo:
The scaling of body parts is central to the expression of morphology across body sizes and to the generation of morphological diversity within and among species. Although patterns of scaling-relationship evolution have been well documented for over one hundred years, little is known regarding how selection acts to generate these patterns. In part, this is because it is unclear the extent to which the elements of log-linear scaling relationships-the intercept or mean trait size and the slope-can evolve independently. Here, using the wing-body size scaling relationship in Drosophila melanogaster as an empirical model, we use artificial selection to demonstrate that the slope of a morphological scaling relationship between an organ (the wing) and body size can evolve independently of mean organ or body size. We discuss our findings in the context of how selection likely operates on morphological scaling relationships in nature, the developmental basis for evolved changes in scaling, and the general approach of using individual-based selection experiments to study the expression and evolution of morphological scaling.
Resumo:
We apply the cognitive hierarchy model of Camerer et al. (Q J Econ 119(3):861-898, 2004)-where players have different levels of reasoning-to Huck et al. (Games Econ Behav 38:240-264, 2002) discrete version of Hamilton and Slutsky (Games Econ Behav 2:29-46, 1990) action commitment game-a duopoly with endogenous timing of entry. We show that, for an empirically reasonable average number of thinking steps, the model rules out Stackelberg equilibria, generates Cournot outcomes including delay, and outcomes where the first mover commits to a quantity higher than Cournot but lower than Stackelberg leader. We show that a cognitive hierarchy model with quantal responses can explain the most important features of the experimental data on the action commitment game in (2002). In order to gauge the success of the model in fitting the data, we compare it to a noisy Nash model. We find that the cognitive hierarchy model with quantal responses fits the data better than the noisy Nash model.