Abstract
Photoacoustic imaging is a hybrid imaging modality capable of producing contrast similar to optical imaging techniques but with increased penetration depth and resolution in turbid media by encoding the information as acoustic waves. In general, it is important to characterize the performance of a photoacoustic imaging system by parameters such as sensitivity, resolution, and contrast. However, system characterization can extend beyond these metrics by implementing advanced analysis via the crosstalk matrix and singular value decomposition. A method was developed to experimentally measure a matrix that represented the imaging operator for a photoacoustic imaging system. Computations to produce the crosstalk matrix were completed to provide insight into the spatially dependent sensitivity and aliasing for the photoacoustic imaging system. Further analysis of the imaging operator was done via singular value decomposition to estimate the capability of the imaging system to reconstruct objects and the inherent sensitivity to those objects. The results provided by singular value decomposition were compared to SVD results from a de-noised imaging operator to estimate the number of measurable singular vectors for the system. These characterization techniques can be broadly applied to any photoacoustic system and, with regards to the studied system, could be used as a basis for improvements to future iterations.
Highlights
1.1 Background Photoacoustic imaging (PAI) is a non-ionizing imaging modality that produces images based on the preferential absorption of optical energy in an absorber by means of the photoacoustic effect
We have previously reported on a method to calibrate a 3D photoacoustic imaging system by way of the translation of a point source through the imaging volume [15]
In the previous work, the individual transducer sensitivities were incorporated into the image reconstruction process to correct for potential non-uniformity in image contrast that might arise due to non-uniform transducer sensitivity to object space
Summary
1.1 Background Photoacoustic imaging (PAI) is a non-ionizing imaging modality that produces images based on the preferential absorption of optical energy in an absorber by means of the photoacoustic effect. The optical energy is deposited rapidly allowing the thermal confinement condition to be met, which facilitates the thermo-elastic expansion of the absorbing structure leading to an outwardly propagating transient bipolar pressure wave [3]. Information is contained within the pressure wave regarding the location, size, shape, and optical properties of the absorbing objects [4]. Using the time-domain measurements acquired by acoustic transducers, an image of the distribution of optical absorbers inside the target volume can be inferred using an image reconstruction algorithm [5,6,7,8,9,10]
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