Estimation of dynamically evolving ellipsoids with applications to medical imaging

The estimation of dynamically evolving ellipsoids from noisy lower-dimensional projections is examined. In particular, this work describes a model-based approach using geometric reconstruction and recursive estimation techniques to obtain a dynamic estimate of left-ventricular ejection fraction from a gated set of planar myocardial perfusion images. The proposed approach differs from current ejection fraction estimation techniques both in the imaging modality used and in the subsequent processing which yields a dynamic ejection fraction estimate. For this work, the left ventricle is modeled as a dynamically evolving three-dimensional (3-D) ellipsoid. The left-ventricular outline observed in the myocardial perfusion images is then modeled as a dynamic, two-dimensional (2-D) ellipsoid, obtained as the projection of the former 3-D ellipsoid. This data is processed in two ways: first, as a 3-D dynamic ellipsoid reconstruction problem; second, each view is considered as a 2-D dynamic ellipse estimation problem and then the 3-D ejection fraction is obtained by combining the effective 2-D ejection fractions of each view. The approximating ellipsoids are reconstructed using a Rauch-Tung-Striebel smoothing filter, which produces an ejection fraction estimate that is more robust to noise since it is based on the entire data set; in contrast, traditional ejection fraction estimates are based only on true frames of data. Further, numerical studies of the sensitivity of this approach to unknown dynamics and projection geometry are presented, providing a rational basis for specifying system parameters. This investigation includes estimation of ejection fraction from both simulated and real data.     

A proposal for minimum detectable compartment in MIRD dosimetry modelling

The accuracy of radiation dose estimates from radiopharmaceutical administrations has recently become more important for three main reasons: (i) clinical providers are demanding more information on diagnostic procedures; (ii) regulatory groups are scrutinizing dosimetry for research subjects; and (iii) accurate organ doses are crucial in therapeutic administrations. These dose estimates are a sensitive function of the residence times. Because most clinical data acquisition protocols are limited to the first 24 h after dose administration, the area under the remainder of the time-activity curve (TAC) must be estimated. Estimation methods range from assuming physical decay only (overly conservative) to extrapolating end point physiological kinetics (overly liberal). This study demonstrates how much the results from these two methods vary and develops an alternative method which more accurately estimates this remainder term. A method, called the minimum detectable compartment (MDC), is constructed so that an accurate dose estimate can be made with a realistic measure of the remainder term. The method for determining MDC uses standard hypothesis testing. Using an analogue of the traditional minimal detectable activity calculation, a model with and without constant compartments is fitted to the TAC. The size of the constant compartment is varied until the relative likelihood of the two models meets the desired measure of power and sensitivity. Computer simulations of a simple mono-exponential are used to demonstrate the MDC as a function of the model, the number of data points, the range of the data and the noise in the data. The MDC is a very sensitive function of the data range. It falls by more than 50% when the data range is increased from two to three half-lives. In addition, the MDC is moderately sensitive to the noise in the data and relatively insensitive to the number of data points. These findings suggest that the MDC method can also be uses a priori to indicate what type of data collection regimen is necessary to achieve a certain accuracy.     

Third-world managers' attitudes toward pollution.

Examined pollution awareness and concern over pollution among 120 Indian managers from several industries. Pollution attitudes were measured by questionnaire responses to the open-ended question, "What is your firm's position in regard to pollution of the environment (in your own words)?" Responses were content analyzed and coded into 3 categories: (a) nonaware (51%), (b) aware-lacking concern (30%), and (c) aware-concerned (19%). Pollution attitudes displayed significant relationships with both individual and organizational variables. It is concluded that although pollution is becoming a serious problem in India, awareness and concern are lagging compared to the more developed countries. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Wear and lubrication in an artificial knee joint replacement

A theoretical study is made of the lubrication mechanism occuring in knee joint replacement under restricted motion. The idealised model has been shown to produce results, consistent with those in normal situations. Effects of increase in concentration of suspended particles in the analysis are similar to that of increase in concentration of hyaluronic acid molecules in synovial fluid. Important deductions are made for load capacity and volume wear rate and it has been shown that the slip velocity plays an important role in maintaining the self-adjusting nature of human joints.     

Multilayer carbon foils for cyclotron beam extraction

The TRIUMF Applied Technology Group operates high-power industrial cyclotrons for commercial radioisotope production. Two of these cyclotrons, TR30-1 and TR30-2, are capable of accelerating H⁻ ions to an energy of 30 MeV and beam currents in excess of 1000 μA. For many years, amorphous carbon foils of approximately 2.0 μm thickness have been utilized to extract proton beams from these accelerators.Novel multilayer foils consisting of layers of amorphous and diamond-like carbon (DLC) of 2.0±0.2 μm thickness were manufactured in-house by carbon arc and pulsed laser deposition, respectively. In the TR30 cyclotrons, the new composite foils with 25% DLC content show a three times longer lifetime than the purely amorphous foils, while maintaining their excellent physical and mechanical characteristics during irradiation.     

Distributed optimization with arbitrary local solvers

With the growth of data and necessity for distributed optimization methods, solvers that work well on a single machine must be re-designed to leverage distributed computation. Recent work in this area has been limited by focusing heavily on developing highly specific methods for the distributed environment. These special-purpose methods are often unable to fully leverage the competitive performance of their well-tuned and customized single machine counterparts. Further, they are unable to easily integrate improvements that continue to be made to single machine methods. To this end, we present a framework for distributed optimization that both allows the flexibility of arbitrary solvers to be used on each (single) machine locally and yet maintains competitive performance against other state-of-the-art special-purpose distributed methods. We give strong primal–dual convergence rate guarantees for our framework that hold for arbitrary local solvers. We demonstrate the impact of local solver selection both theoretically and in an extensive experimental comparison. Finally, we provide thorough implementation details for our framework, highlighting areas for practical performance gains.