Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

Effect of vascular targeting agent in rat tumor model: dynamic contrast-enhanced versus diffusion-weighted MR imaging

PURPOSE: To compare dynamic contrast material-enhanced magnetic resonance (MR) imaging and diffusion-weighted MR imaging for noninvasive evaluation of early and late effects of a vascular targeting agent in a rat tumor model. MATERIALS AND METHODS: The study protocol was approved by the local ethics committee for animal care and use. Thirteen rats with one rhabdomyosarcoma in each flank (26 tumors) underwent dynamic contrast-enhanced imaging and diffusion-weighted echo-planar imaging in a 1.5-T MR unit before intraperitoneal injection of combretastatin A4 phosphate and at early (1 and 6 hours) and later (2 and 9 days) follow-up examinations after the injection. Histopathologic examination was performed at each time point. The apparent diffusion coefficient (ADC) of each tumor was calculated separately on the basis of diffusion-weighted images obtained with low b gradient values (ADC(low); b = 0, 50, and 100 sec/mm(2)) and high b gradient values (ADC(high); b = 500, 750, and 1000 sec/mm(2)). The difference between ADC(low) and ADC(high) was used as a surrogate measure of tissue perfusion (ADC(low) - ADC(high) = ADC(perf)). From the dynamic contrast-enhanced MR images, the volume transfer constant k and the initial slope of the contrast enhancement-time curve were calculated. For statistical analyses, a paired two-tailed Student t test and linear regression analysis were used. RESULTS: Early after administration of combretastatin, all perfusion-related parameters (k, initial slope, and ADC(perf)) decreased significantly (P < .001); at 9 days after combretastatin administration, they increased significantly (P < .001). Changes in ADC(perf) were correlated with changes in k (R(2) = 0.46, P < .001) and the initial slope (R(2) = 0.67, P < .001). CONCLUSION: Both dynamic contrast-enhanced MR imaging and diffusion-weighted MR imaging allow monitoring of perfusion changes induced by vascular targeting agents in tumors. Diffusion-weighted imaging provides additional information about intratumoral cell viability versus necrosis after administration of combretastatin.

Dynamic contrast-enhanced and diffusion-weighted MRI for early detection of tumoral changes in single-dose and fractionated radiotherapy: evaluation in a rat rhabdomyosarcoma model

We aimed to examine different intratumoral changes after single-dose and fractionated radiotherapy, using diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in a rat rhabdomyosarcoma model. Four WAG/Rij rats with rhabdomyosarcomas in the flanks received single-dose radiotherapy of 8 Gy, and four others underwent fractionated radiotherapy (five times 3 Gy). In rats receiving single-dose radiotherapy, a significant perfusion decrease was found in the first 2 days post-treatment, with slow recuperation afterwards. No substantial diffusion changes could be seen; tumor growth delay was 12 days. The rats undergoing fractionated radiotherapy showed a similar perfusion decrease early after the treatment. However, a very strong increase in apparent diffusion coefficient occurred in the first 10 days; growth delay was 18 days. DW-MRI and DCE-MRI can be used to show early tumoral changes induced by radiotherapy. Single-dose and fractionated radiotherapy induce an immediate perfusion effect, while the latter induces more intratumoral necrosis.

Dynamic Synchronization: A Synchronization Model through Behavioral Reflection

In conventional software applications, synchronization code is typically interspersed with functional code, thereby impacting understandability and maintainability of the code base. At the same time, the synchronization defined statically in the code is not capable of adapting to different runtime situations. We propose a new approach to concurrency control which strictly separates the functional code from the synchronization requirements to be used and which adapts objects to be synchronized dynamically to their environment. First-class synchronization specifications express safety requirements, and a dynamic synchronization system dynamically adapts objects to different runtime situations. We present an overview of a prototype of our approach together with several classical concurrency problems, and we discuss open issues for further research.

Impact of epinephrine and norepinephrine on two dynamic indices in a porcine hemorrhagic shock model

Abstract BACKGROUND: Pulse pressure variations (PPVs) and stroke volume variations (SVVs) are dynamic indices for predicting fluid responsiveness in intensive care unit patients. These hemodynamic markers underscore Frank-Starling law by which volume expansion increases cardiac output (CO). The aim of the present study was to evaluate the impact of the administration of catecholamines on PPV, SVV, and inferior vena cava flow (IVCF). METHODS: In this prospective, physiologic, animal study, hemodynamic parameters were measured in deeply sedated and mechanically ventilated pigs. Systemic hemodynamic and pressure-volume loops obtained by inferior vena cava occlusion were recorded. Measurements were collected during two conditions, that is, normovolemia and hypovolemia, generated by blood removal to obtain a mean arterial pressure value lower than 60 mm Hg. At each condition, CO, IVCF, SVV, and PPV were assessed by catheters and flow meters. Data were compared between the conditions normovolemia and hypovolemia before and after intravenous administrations of norepinephrine and epinephrine using a nonparametric Wilcoxon test. RESULTS: Eight pigs were anesthetized, mechanically ventilated, and equipped. Both norepinephrine and epinephrine significantly increased IVCF and decreased PPV and SVV, regardless of volemic conditions (p < 0.05). However, epinephrine was also able to significantly increase CO regardless of volemic conditions. CONCLUSION: The present study demonstrates that intravenous administrations of norepinephrine and epinephrine increase IVCF, whatever the volemic conditions are. The concomitant decreases in PPV and SVV corroborate the fact that catecholamine administration recruits unstressed blood volume. In this regard, understanding a decrease in PPV and SVV values, after catecholamine administration, as an obvious indication of a restored volemia could be an outright misinterpretation.

A Dynamic Stochastic Frontier Production Model with Time-Varying Efficiency

In this paper we introduce technical efficiency via the intercept that evolve over time as a AR(1) process in a stochastic frontier (SF) framework in a panel data framework. Following are the distinguishing features of the model. First, the model is dynamic in nature. Second, it can separate technical inefficiency from fixed firm-specific effects which are not part of inefficiency. Third, the model allows one to estimate technical change separate from change in technical efficiency. We propose the ML method to estimate the parameters of the model. Finally, we derive expressions to calculate/predict technical inefficiency (efficiency).

Marine Isotope Stage (MIS) 11 results of model data with Community Climate System Model version 3 including the Dynamic Global Vegetation Model (CCSM3-DGVM) in NetCDF format at global and regional scale

The climate of Marine Isotope Stage (MIS) 11, the interglacial roughly 400,000 years ago, is investigated for four time slices, 416, 410, 400, and 394 ka. The overall picture is that MIS 11 was a relatively warm interglacial in comparison to preindustrial, with Northern Hemisphere (NH) summer temperatures early in MIS 11 (416-410 ka) warmer than preindustrial, though winters were cooler. Later in MIS 11, especially around 400 ka, conditions were cooler in the NH summer, mainly in the high latitudes. Climate changes simulated by the models were mainly driven by insolation changes, with the exception of two local feedbacks that amplify climate changes. Here, the NH high latitudes, where reductions in sea ice cover lead to a winter warming early in MIS 11, as well as the tropics, where monsoon changes lead to stronger climate variations than one would expect on the basis of latitudinal mean insolation change alone, are especially prominent. The results support a northward expansion of trees at the expense of grasses in the high northern latitudes early during MIS 11, especially in northern Asia and North America.

Exchange Rate Stabilization and IMF High Interest Rate Policy: A Critical Reconsideration Using a Dynamic Model

This paper examines whether the IMF high interest rate policy was suitable for crisis-ridden East Asian economies. Using an "overshoot" model similar to that of Dornbusch's (1976), it shows that this sort of policy might cause an unnecessary deflationary adjusting process and have no effect on containing the real depreciation of exchange rates in the long run. The study also demonstrates that Thai economic data coincides quite well with the model presented here. Finally, it points out that the high interest policy itself might provoke high risk-premium, the existence of which, in turn, justifies the policy. This means that the policy has a self-fulfilling property. In conclusion, a "one-size-fits-all" adaptation of high interest rate policy in a currency crisis is very dangerous in general, and was inappropriate for East Asia. The desirable policy would have been to let currencies depreciate and keep interest rates stable.