843 resultados para shape descriptors
Resumo:
This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).
Resumo:
This paper addresses the issue of matching statistical and non-rigid shapes, and introduces an Expectation Conditional Maximization-based deformable shape registration (ECM-DSR) algorithm. Similar to previous works, we cast the statistical and non-rigid shape registration problem into a missing data framework and handle the unknown correspondences with Gaussian Mixture Models (GMM). The registration problem is then solved by fitting the GMM centroids to the data. But unlike previous works where equal isotropic covariances are used, our new algorithm uses heteroscedastic covariances whose values are iteratively estimated from the data. A previously introduced virtual observation concept is adopted here to simplify the estimation of the registration parameters. Based on this concept, we derive closed-form solutions to estimate parameters for statistical or non-rigid shape registrations in each iteration. Our experiments conducted on synthesized and real data demonstrate that the ECM-DSR algorithm has various advantages over existing algorithms.
Resumo:
Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.
How Welfare States Shape the Democratic Public: Policy Feedback, Participation, Voting and Attitudes
Resumo:
This crucial volume significantly advances the study of policy feedbacks. With contributions from many subfields and methodological approaches, it offers both sophisticated theorizing and new empirical examples that show how policies make politics in a variety of ways. Innovative research designs provide more convincing inference than ever. And the normative questions engaged about welfare performance, evaluation, participation, and accountability could not be more important or timely in this era of austerity and discord over the future of welfare states.’
Resumo:
Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.
Resumo:
Intestinal bacterial metabolites are an important communication tool between the host immune system and the commensal microbiota to establish mutualism. In a recent paper published in Science, Wendy Garrett and her colleagues report an exciting role of the three most abundant microbial-derived short-chain fatty acids (SCFA), acetic acid, propionic acid and butyric acid, in colonic regulatory T cell (cTreg) homeostasis.
Resumo:
In general, fiscal adjustments are associated with significant reductions in social spending. Hence, the welfare state is not spared from austerity. Because the welfare state is still central to party competition, this is electorally risky. The paper addresses the following questions: Do left parties differ from their centrist and rightist competitors in the design of austerity measures? And does government type has an impact on the extent to which austerity policies rely on social spending cuts? By comparing 17 OECD countries between 1982 and 2009 we show that if governments embark on a path to austerity, their ideology does not have a significant effect on the magnitude of welfare state retrenchment. However, if major opposition parties and interest groups rally against social spending cuts, a broad pro-reform coalition is a crucial precondition for large fiscal consolidation programs to rely on substantial cuts to social security.