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The human skin is the outermost organ of the body. The thickness of the skin can give useful clinical information on its condition. In this thesis the complicated structure of the skin was described and methods of skin thickness measurement critically reviewed. Ultrasound was identified as a non-invasive method having several advantages over the other methods, such as safety, ease of use and low cost. The existing ultrasonic systems have not been successful to quantify the skin structure properly, due to lack of high resolution transducers and the biology of the skin structure. The PZFlex Finite Element Method (FEM) package was used to model the skin, an ultrasonic thickness measurement system, and their interaction, in order to define the system structure and parameters. Initially, the skin was modelled as one planar layer of a linear isotropic material and 5MHz transducer was used to minimize computational effort. A nonplanar structure was then modelled and compared to the planar interface to see the effect of the additional complexity on the backscattered signal and to clarify the axial and lateral resolution requirements for skin thickness measurement. Different front face configurations of the transducer were also modelled to investigate the effect of the geometry on the backscattered signal as a starting point to introduce practical coupling. A more realistic skin structure was then modelled at 80 MHz, by super-imposing a FEM mesh on a micrograph of the skin and the backscattered ultrasound signal from the real skin interfaces compared to a signal from planar interfaces. An appraise of the existing technology was concluded and the requirements for an ideal skin thickness measurement system were then addressed. A monolithic LiNb0b3s transducer incorporating inversion layers (IL) was modelled using PZFlex to investigate the usefulness of these transducers for skin measurement. A novel mathematical 1-D linear systems model was developed for a transducer incorporating one front face inversion layer. This model gave a physical insight into, and more understanding of, the transducer behaviour. It was found that, although ILT's offer improved sensitivity and bandwidth for skin thickness measurement, they suffer from similar problems to conventional devices and a new transducer technology is needed for ultra high resolution applications on real skin surfaces. The new theory offers substantial base for the design of ILT' s, which will have significant applications in other areas, such as harmonic imaging and multi-frequency sonar.

The high power intensities in HIFU often result in bubble production, either through cavitation or boiling, which are believed to be a primary contributor to tissue necrosis. Bubbles are associated with the bright hyperechoic regions in ultrasound B-mode images. As the only changes observed on tissue are subtle during treatment, some HIFU therapy protocols rely on the observation of significant brightness changes as the indicator of tissue lesions. The occurrence of a distinct hyperechoic region around the focus is often associated with cavitation. In general, the hyperechoic regions show good correlation with ablated tissue (observed directly following subsequent removal of the tumour in an operation, or using MRI), but the sensitivity of this techniques is sub-optimal. Reliable detection of cavitation and a method to distinguish between different types of events is therefore, an important goal for better control of the treatment. This thesis presents a novel method to provide detection of cavitation activity as an aid to assisting treatment. The image intensity information is used to identify hyperechoic regions spatially and temporally. However, hyperechoic regions may appear for reasons other than cavitation - for example because of tissue interfaces. The spectral information is useful to distinguish from other events and thermal generation of bubbles. Thus the spectral estimation methods are becoming of increasing interest in early and robust detection of cavitation activity. There are three main contributions related to this thesis: identifying the boundaries and maintaining a history of cavitation events from their brightness and intensity statistics through using a probabilistic method, determining not just the presence of cavitation but also its local changes at a high spatial resolution through analysing spectrally the RF signals from the imaging transducer on a pixel by pixel basis, and finally combining the advantages of both methods to improve the overall reliability of automatic cavitation detection. In addition, the spectral information extracted here is capable potentially of distinguishing between cavitation and boiling. The method is assessed using a simulation of a synthesised cavitation, and the applied to detect cavitation following HIFU in ex-vivo calf liver.