Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.

PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima

Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

A robust reference signal generator for synchronized ventricular assist devices

Ventricular assist devices (VADs) are blood pumps that offer an option to support the circulation of patients with severe heart failure. Since a failing heart has a remaining pump function, its interaction with the VAD influences the hemodynamics. Ideally, the heart's action is taken into account for actuating the device such that the device is synchronized to the natural cardiac cycle. To realize this in practice, a reliable real-time algorithm for the automatic synchronization of the VAD to the heart rate is required. This paper defines the tasks such an algorithm needs to fulfill: the automatic detection of irregular heart beats and the feedback control of the phase shift between the systolic phases of the heart and the assist device. We demonstrate a possible solution to these problems and analyze its performance in two steps. First, the algorithm is tested using the MIT-BIH arrhythmia database. Second, the algorithm is implemented in a controller for a pulsatile and a continuous-flow VAD. These devices are connected to a hybrid mock circulation where three test scenarios are evaluated. The proposed algorithm ensures a reliable synchronization of the VAD to the heart cycle, while being insensitive to irregularities in the heart rate.

Wie robust sind Arbeitsbeziehung und Therapieerfolg ineinander verzahnt? Eine metaanalytische Bestandsaufnahme

Hintergrund: Die therapeutische Arbeitsbeziehung (alliance) ist das meistuntersuchte Prozessmerkmal in der Psychotherapieforschung schlecht hin und zeigt sich als robuster Prädiktor für Therapieerfolg (r = .275). Fragestellung: Welche Einflussfaktoren (wie beispielsweise kognitive Verhaltenstherapie in randomisierten Trials) moderieren den Zusammenhang zwischen Allianz und Erfolg? Methode: Basierend auf über zweihundert in Englisch, deutsch, französisch und italienisch verfassten Primärstudien werden mögliche Moderatoren metaanalytisch untersucht, die den Zusammenhang zwischen Allianz und Therapieerfolg beeinflussen. Resultate: Der aktuelle Stand der APA-Taskforce kann folgendermaßen zusammengefasst werden: (a) Erhebungszeitpunkt der Allianz, (b) Anzahl Patienten pro Therapeut, (b) Forscherinteresse, (c) Therapieerfolg = Abbrüche, (d) Anteil der Nicht-Weißen Bevölkerung und (e) Alkohol und -Substanzmissbrauch als Ausschlusskriterium, beeinflussen den Zusammenhang zwischen Allianz und Erfolg. Folgenden Aspekten moderieren den Zusammenhang zwischen Allianz und Therapieerfolg nicht: (a) Allianz-Messmittel und Erhebungsperspektive (Patient, Therapeut oder Beobachter), (b) Doktorarbeiten, (c) Therapietradition (Kognitive-Behaviorale, Interpersonale, psychodynamische Therapien), (d) randomisiert kontrollierte Trials, (e) manualisierte Therapien, (f ) störungsspezifische Erfolgsmessung, (g) Persönlichkeitsstörungen, (h) nicht-englisch sprachliche Manuskripte. Diskussion: Durch die Moderatoren kann ein beträchtlicher Anteil der Heterogenität erklärt werden. Die Beziehung zwischen Allianz und Therapieerfolg wird durch konzeptuelle biopsychosozialer Faktoren mitbeeinflusst.

Highly pathogenic adapted HIV-1 strains limit host immunity and dictate rapid disease progression.

OBJECTIVE: The study of HIV-1 rapid progressors has been limited to specific case reports. Nevertheless, identification and characterization of the viral and host factors involved in rapid progression are crucial when attempting to uncover the correlates of rapid disease outcome. DESIGN: We carried out comparative functional analyses in rapid progressors (n = 46) and standard progressors (n = 46) early after HIV-1 seroconversion (≤1 year). The viral traits tested were viral replicative capacity, co-receptor usage, and genomic variation. Host CD8 T-cell responses, humoral activity, and HLA immunogenetic markers were also determined. RESULTS: Our data demonstrate an unusual convergence of highly pathogenic HIV-1 strains in rapid progressors. Compared with standard progressors, rapid progressor viral strains show higher in-vitro replicative capacity (81.5 vs. 67.9%; P = 0.025) and greater X4/DM co-receptor usage (26.3 vs. 2.8%; P = 0.006) in early infection. Limited or absent functional HIV-1 CD8 T-cell responses and neutralizing activity were measured in rapid progressors. Moreover, the increase in common HLA allele-restricted CD8 T-cell escape mutations in rapid progressors acts as a signature of uncontrolled HIV-1 replication and early impairment of adaptive cellular responses. CONCLUSION: Our data support a dominant role for viral factors in rapid progressors. Robust HIV-1 replication and intrinsic viral properties limit host adaptive immune responses, thus driving rapid disease progression.

Robust estimates of climate-induced hydrological change in a temperate mountainous region

A sustainable water resources management depends on sound information about the impacts of climate change. This information is, however, not easily derived because natural runoff variability interferes with the climate change signal. This study presents a procedure that leads to robust estimates of magnitude and Time Of Emergence (TOE) of climate-induced hydrological change that also account for the natural variability contained in the time series. Firstly, natural variability of 189 mesoscale catchments in Switzerland is sampled for 10 ENSEMBLES scenarios for the control (1984–2005) and two scenario periods (near future: 2025–2046, far future: 2074–2095) applying a bootstrap procedure. Then, the sampling distributions of mean monthly runoff are tested for significant differences with the Wilcoxon-Mann–Whitney test and for effect size with Cliff’s delta d. Finally, the TOE of a climate change induced hydrological change is determined when at least eight out of the ten hydrological projections significantly differ from natural variability. The results show that the TOE occurs in the near future period except for high-elevated catchments in late summer. The significant hydrological projections in the near future correspond, however, to only minor runoff changes. In the far future, hydrological change is statistically significant and runoff changes are substantial. Temperature change is the most important factor determining hydrological change in this mountainous region. Therefore, hydrological change depends strongly on a catchment’s mean elevation. Considering that the hydrological changes are predicted to be robust in the near future highlights the importance of accounting for these changes in water resources planning.

Three-Dimensional Mechanics of Yakutat Convergence in the Southern Alaskan Plate Corner

Three-dimensional numerical models are used to investigate the mechanical evolution of the southern Alaskan plate corner where the Yakutat and the Pacific plates converge on the North American plate. The evolving model plate boundary consists of Convergent, Lateral, and Subduction subboundaries with flow separation of incoming material into upward or downward trajectories forming dual, nonlinear advective thermal/mechanical anomalies that fix the position of major subaerial mountain belts. The model convergent subboundary evolves into two teleconnected orogens: Inlet and Outlet orogens form at locations that correspond with the St. Elias and the Central Alaska Range, respectively, linked to the East by the Lateral boundary. Basins form parallel to the orogens in response to the downward component of velocity associated with subduction. Strain along the Lateral subboundary varies as a function of orogen rheology and magnitude and distribution of erosion. Strain-dependent shear resistance of the plate boundary associated with the shallow subduction zone controls the position of the Inlet orogen. The linkages among these plate boundaries display maximum shear strain rates in the horizontal and vertical planes where the Lateral subboundary joins the Inlet and Outlet orogens. The location of the strain maxima shifts with time as the separation of the Inlet and Outlet orogens increases. The spatiotemporal predictions of the model are consistent with observed exhumation histories deduced from thermochronology, as well as stratigraphic studies of synorogenic deposits. In addition, the complex structural evolution of the St Elias region is broadly consistent with the predicted strain field evolution. Citation: Koons, P. O., B. P. Hooks, T. Pavlis, P. Upton, and A. D. Barker (2010), Three-dimensional mechanics of Yakutat convergence in the southern Alaskan plate corner, Tectonics, 29, TC4008, doi: 10.1029/2009TC002463.

A Global Trend towards Democratic Convergence? A Lijphartian Analysis of Advanced Democracies.

The article offers a systematic analysis of the comparative trajectory of international democratic change. In particular, it focuses on the resulting convergence or divergence of political systems, borrowing from the literatures on institutional change and policy convergence. To this end, political-institutional data in line with Arend Lijphart’s (1999, 2012) empirical theory of democracy for 24 developed democracies between 1945 and 2010 are analyzed. Heteroscedastic multilevel models allow for directly modeling the development of the variance of types of democracy over time, revealing information about convergence, and adding substantial explanations. The findings indicate that there has been a trend away from extreme types of democracy in single cases, but no unconditional trend of convergence can be observed. However, there are conditional processes of convergence. In particular, economic globalization and the domestic veto structure interactively influence democratic convergence.

Robust meta-analytic-predictive priors in clinical trials with historical control information.

Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.