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Phantom-based image quality test methods for photoacoustic imaging systems

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Abstract. As photoacoustic imaging (PAI) technologies advance and applications arise, there is increasing need for standardized approaches to provide objective, quantitative performance assessment at various stages of the product development… Click to show full abstract

Abstract. As photoacoustic imaging (PAI) technologies advance and applications arise, there is increasing need for standardized approaches to provide objective, quantitative performance assessment at various stages of the product development and clinical translation process. We have developed a set of performance test methods for PAI systems based on breast-mimicking tissue phantoms containing embedded inclusions. Performance standards for mature imaging modalities [magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound] were used to guide selection of critical PAI image quality characteristics and experimental methods. Specifically, the tests were designed to address axial, lateral, and elevational spatial resolution, signal uniformity, penetration depth, sensitivity, spatial measurement accuracy, and PAI-ultrasound coregistration. As an initial demonstration of the utility of these test methods, we characterized the performance of a modular, bimodal PAI-ultrasound system using four clinical ultrasound transducers with varying design specifications. Results helped to inform optimization of acquisition and data processing procedures while providing quantitative elucidation of transducer-dependent differences in image quality. Comparison of solid, tissue-mimicking polymer phantoms with those based on Intralipid indicated the superiority of the former approach in simulating real-world conditions for PAI. This work provides a critical foundation for the establishment of well-validated test methods that will facilitate the maturation of PAI as a medical imaging technology.

Keywords: pai; test methods; image quality; test

Journal Title: Journal of Biomedical Optics
Year Published: 2017

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