Abstract

Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of such data is often hampered by opaque processing algorithms, which are challenging to verify and validate from a user perspective. Furthermore, such tools are inflexible, often locking users into a restricted set of processing motifs, which may not be able to accommodate the demands of diverse experiments. To address these needs, we have developed a Reconstruction, Analysis, and Filtering Toolbox to support the analysis of photoacoustic imaging data. The toolbox includes several algorithms to improve the overall quantification of photoacoustic imaging, including non-negative constraints and multispectral filters. We demonstrate various use cases, including dynamic imaging challenges and quantification of drug effect, and describe the ability of the toolbox to be parallelized on a high performance computing cluster.

Highlights

  • MSOT may be thought of as optically-encoded ultrasound; an object under brief, intense illumination absorbs some of the illuminating energy, converting some of that energy into ­heat[1,2]

  • We address several of these problems and believe that this new tool will provide a foundation for the future development of photoacoustic imaging, and that further development of the RAFT will continue to expand its capabilities

  • This may be attributed to the problem of aliasing; the direct interpolated model matrix i­nversion28 (dIMMI) method allocates additional sampling points along the integral curve during model calculation, acting as an anti-aliasing filter, which reduces the incidence of high-frequency artifacts exacerbated by the differentiation step

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Summary

Introduction

MSOT may be thought of as optically-encoded ultrasound; an object under brief, intense illumination absorbs some of the illuminating energy, converting some of that energy into ­heat[1,2]. This heat induces transient thermoelastic expansion, creating a pressure wave, which travels outward from the point of absorption. Of the original pressure image provides a measure of energy deposition by the original illumination, which may be related across multiple illumination wavelengths to yield an overall spectral image. The field assumes a maximum energy deposition of 20 mJ/cm[2] at skin surface, and many low-energy laser shots may be substituted for few high-energy laser s­ hots[19,20]

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