Waveform Engineering for Performance Improvement of Photoacoustic Imaging and Detection Systems

Abstract

Various imaging and detection modalities and systems are currently in use and progress has been made on enhancing the performance of those systems. Signal to Noise Ratio (SNR) and resolution or profilometric information are important metrics of performance in such systems. Photoacoustic imaging is a rapidly emerging imaging modality that combines the high contrast of pure optical imaging and high resolution of ultrasound imaging into a single modality. Much research has been done on improving the performance of photoacoustic imaging systems, such as matched-filtering, averaging, etc. However, waveform engineering methods for photoacoustic imaging have not received much attention in the literature to date. This thesis will apply techniques of waveform engineering to photoacoustic imaging and detection systems. Design of optimal waveforms and receiver-filters for photoacoustic imaging systems will be addressed. Specifically, this thesis will: 1. Develop and analyze the theory of optimal waveform engineering for SNR of photoacoustic systems. 2. Analyze the performance of commonly used input waveforms and compare with optimal SNR waveforms. 3. Develop and analyze the theory of optimal waveform design for profilometric information or parameter estimation of photoacoustic imaging systems.