Ultrasound Transient Shear Wave Elasticity Imaging for Tendon Tissue

Degeneration of tendon tissue is a common cause of tendon dysfunction with the symptoms of repeated episodes of pain and palpable increase of tendon thickness. Tendon mechanical properties are directly related to its physiological composition and the structural organization of the interior collagen fibers which could be altered by tendon degeneration due to overuse or injury. Thus, measuring mechanical properties of tendon tissue may represent a quantitative measurement of pain, reduced function, and tissue health. Ultrasound elasticity imaging has been developed in the last two decades and has proved to be a promising tool for tissue elasticity imaging. To date, however, well established protocols of tendinopathy elasticity imaging for diagnosing tendon degeneration in early stages or late stages do not exist. This thesis describes the re-creation of one dynamic ultrasound elasticity imaging method and the development of an ultrasound transient shear wave elasticity imaging platform for tendon and other musculoskeletal tissue imaging. An experimental mechanical stage with proper supporting systems and accurate translating stages was designed and made. A variety of high-quality tissue-mimicking phantoms were made to simulate homogeneous and heterogeneous soft tissues as well as tendon tissues. A series of data acquisition and data processing programs were developed to collect the displacement data from the phantom and calculate the shear modulus and Young’s modulus of the target. The imaging platform was found to be capable of conducting comparative measurements of the elastic parameters of the phantoms and quantitatively mapping elasticity onto ultrasound B-Mode images. This suggests the system has great potential for not only benefiting individuals with tendinopathy with an earlier detection, intervention and better rehabilitation, but also for providing a medical tool for quantification of musculoskeletal tissue dysfunction in other regions of the body such as the shoulder, elbow and knee.

A Novel Fiber Delay Line Buffering Architecture for Optical Packet Switching

Due to the lack of optical random access memory, optical fiber delay line (FDL) is currently the only way to implement optical buffering. Feed-forward and feedback are two kinds of FDL structures in optical buffering. Both have advantages and disadvantages. In this paper, we propose a more effective hybrid FDL architecture that combines the merits of both schemes. The core of this switch is the arrayed waveguide grating (AWG) and the tunable wavelength converter (TWC). It requires smaller optical device sizes and fewer wavelengths and has less noise than feedback architecture. At the same time, it can facilitate preemptive priority routing which feed-forward architecture cannot support. Our numerical results show that the new switch architecture significantly reduces packet loss probability.

Cross-Layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks

In this paper, a cross-layer solution for packet size optimization in wireless sensor networks (WSN) is introduced such that the effects of multi-hop routing, the broadcast nature of the physical wireless channel, and the effects of error control techniques are captured. A key result of this paper is that contrary to the conventional wireless networks, in wireless sensor networks, longer packets reduce the collision probability. Consequently, an optimization solution is formalized by using three different objective functions, i.e., packet throughput, energy consumption, and resource utilization. Furthermore, the effects of end-to-end latency and reliability constraints are investigated that may be required by a particular application. As a result, a generic, cross-layer optimization framework is developed to determine the optimal packet size in WSN. This framework is further extended to determine the optimal packet size in underwater and underground sensor networks. From this framework, the optimal packet sizes under various network parameters are determined.