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.

Laccase bio-grafting a versatile modification tool from green chemistry technologies

Today more than 99% of plastics are petroleum-based because of availability and cost of the raw material. The durability of these disposed plastics contributes to the environmental problems as waste and their persistence in the environment causes deleterious effects on the ecosystem. Environmental pollution awareness and the demand for green technology have drawn considerable attention of both academia and industry into biodegradable polymers. In this regard green chemistry technology has the potential to provide solution to this problematic issue. Laccase bio-grafting has recently been the focus of green chemistry technologies due to the growing environmental concerns, legal restrictions and increasing availability of scientific knowledge. In the last several years, research covering various applications of laccases has been increased rapidly particularly in the field of grafting. In principle, laccase-assisted graft co-polymerization may impart a variety of new functionalities to a polymer. The modified polymers through grafting have a bright future and their development is practically boundless. In present work, novel biodegradable graft copolymers combining the advantages of bacterial cellulose backbone and PHB side chains will be prepared by introducing enzymatic grafting technique. The present research will be a first step in the biopolymer modification. To date no report has been found in literature explaining the enzymatic grafting of PHAs. The technique would also provide an efficient modulation approach to improve the biodegradability and biocompatibility of the graft copolymer. The newly grafted copolymers will exhibit unique functionalities with wider range of potential applications mainly in tissue engineering, biosensors, pharmaceutical industry (drug delivery systems) and bio-plastics.

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.