Performance Evaluation of a Statistical and a Neural Network Model for Nonrigid Shape-Based Registration

Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.

Understanding what drives the purchase decision in pension and investment products

The aims of this paper are to first seek an understanding of consumer decision-making when purchasing pension and investment products, and second to ascertain how this decision-making affects the consumer's choice of distribution route. The study employed both focus groups and postal questionnaire survey methods based on the framework of a classical decision-making model that investigated problem recognition, information search, evaluation tools used and post-purchase. The findings show that the decision-making process experience differed to a lesser or greater degree depending on the distribution route. The majority of respondents had recognised the need to make a purchase decision long before seeking information. Younger respondents on all incomes believed that they must make some pension provision for themselves as opposed to relying on the government's retirement provision. Many changed channels for information searches, but tended to settle with the Independent Financial Adviser (IFA). The two main evaluation tools for pension and investment were found to be the ‘charges’ and ‘historic fund performance’. The vast majority of respondents reiterated their worry that the outcomes would not be known until retirement. In terms of analysis by the level of ‘financial literacy’, respondents who scored in the upper quartile were more inclined to be on a higher income, less inclined to evaluate on charges and more proactive in discussing the investment strategy of their pension fund. Respondents who scored in the lower quartile had opposite results. One of the implications of these findings is that the younger respondents’ recognition of pension savings favours the government's intention to reverse the existing balance of pension distribution. The other main implication is that the findings will be of help to managers in appreciating the dominance of the IFA channel by providing an explanation of why consumers choose this route, and, additionally, can assist direct marketing managers in identifying customers who will be more likely to use multichannel or single-channel shoppers. It can also help the marketing manager increase the usage of different channels by addressing the factors driving the purchase decision and distribution choice.

Design, analysis and evaluation of sigma-delta based beamformers for medical ultrasound imaging applications

The inherent analogue nature of medical ultrasound signals in conjunction with the abundant merits provided by digital image acquisition, together with the increasing use of relatively simple front-end circuitries, have created considerable demand for single-bit  beamformers in digital ultrasound imaging systems. Furthermore, the increasing need to design lightweight ultrasound systems with low power consumption and low noise, provide ample justification for development and innovation in the use of single-bit  beamformers in ultrasound imaging systems. The overall aim of this research program is to investigate, establish, develop and confirm through a combination of theoretical analysis and detailed simulations, that utilize raw phantom data sets, suitable techniques for the design of simple-to-implement hardware efficient  digital ultrasound beamformers to address the requirements for 3D scanners with large channel counts, as well as portable and lightweight ultrasound scanners for point-of-care applications and intravascular imaging systems. In addition, the stability boundaries of higher-order High-Pass (HP) and Band-Pass (BP) Σ−Δ modulators for single- and dual- sinusoidal inputs are determined using quasi-linear modeling together with the describing-function method, to more accurately model the  modulator quantizer. The theoretical results are shown to be in good agreement with the simulation results for a variety of input amplitudes, bandwidths, and modulator orders. The proposed mathematical models of the quantizer will immensely help speed up the design of higher order HP and BP Σ−Δ modulators to be applicable for digital ultrasound beamformers. Finally, a user friendly design and performance evaluation tool for LP, BP and HP  modulators is developed. This toolbox, which uses various design methodologies and covers an assortment of  modulators topologies, is intended to accelerate the design process and evaluation of  modulators. This design tool is further developed to enable the design, analysis and evaluation of  beamformer structures including the noise analyses of the final B-scan images. Thus, this tool will allow researchers and practitioners to design and verify different reconstruction filters and analyze the results directly on the B-scan ultrasound images thereby saving considerable time and effort.