Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Coronary collateral function in the transplanted heart: propensity score matching with coronary artery disease

The function of the coronary collateral circulation in heart transplant patients has not been investigated in a controlled fashion. Since it partly belongs to the microcirculation, which is affected by transplant vasculopathy, the hypothesis was tested that the coronary collateral circulation in heart transplant recipients is less developed than in coronary artery disease (CAD) patients.

A 3-center comparison of 1-year mortality outcomes between transcatheter aortic valve implantation and surgical aortic valve replacement on the basis of propensity score matching among intermediate-risk surgical patients

This study sought to compare all-cause mortality in patients at intermediate surgical risk undergoing transcatheter aortic valve implantation (TAVI) or surgical aortic valve replacement (SAVR).

Selection of Matching Variables in Community Health Intervention Trials

In a matched experimental design, the effectiveness of matching in reducing bias and increasing power depends on the strength of the association between the matching variable and the outcome of interest. In particular, in the design of a community health intervention trial, the effectiveness of a matched design, where communities are matched according to some community characteristic, depends on the strength of the correlation between the matching characteristic and the change in the health behavior being measured. We attempt to estimate the correlation between community characteristics and changes in health behaviors in four datasets from community intervention trials and observational studies. Community characteristics that are highly correlated with changes in health behaviors would potentially be effective matching variables in studies of health intervention programs designed to change those behaviors. Among the community characteristics considered, the urban-rural character of the community was the most highly correlated with changes in health behaviors. The correlations between Per Capita Income, Percent Low Income & Percent aged over 65 and changes in health behaviors were marginally statistically significant (p < 0.08).

From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition

In this work, we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pursuit algorithm and called dependency multichannel matching pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is implied by the electric leadfield. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during different physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.

Synchronisation of the EDML and EDC ice cores for the last 52 kyr by volcanic signature matching

A common time scale for the EPICA ice cores from Dome C (EDC) and Dronning Maud Land (EDML) has been established. Since the EDML core was not drilled on a dome, the development of the EDML1 time scale for the EPICA ice core drilled in Dronning Maud Land was based on the creation of a detailed stratigraphic link between EDML and EDC, which was dated by a simpler 1D ice-flow model. The synchronisation between the two EPICA ice cores was done through the identification of several common volcanic signatures. This paper describes the rigorous method, using the signature of volcanic sulfate, which was employed for the last 52 kyr of the record. We estimated the discrepancies between the modelled EDC and EDML glaciological age scales during the studied period, by evaluating the ratio R of the apparent duration of temporal intervals between pairs of isochrones. On average R ranges between 0.8 and 1.2 corresponding to an uncertainty of up to 20% in the estimate of the time duration in at least one of the two ice cores. Significant deviations of R up to 1.4–1.5 are observed between 18 and 28 kyr before present (BP), where present is defined as 1950. At this stage our approach does not allow us unequivocally to find out which of the models is affected by errors, but assuming that the thinning function at both sites and accumulation history at Dome C (which was drilled on a dome) are correct, this anomaly can be ascribed to a complex spatial accumulation variability (which may be different in the past compared to the present day) upstream of the EDML core.