Aug 2026· Scientific Data· Vol 13· 0 citations· 42 references
Medicine
TL;DR
This work presents a dataset of 30 tissue-mimicking phantoms imaged using three different photoacoustic systems and believes that OpenQPAIData enables the benchmarking of both acoustic and optical inverse solvers and supports the development of image quality assessment metrics for photoacoustic imaging.
Abstract
The goal of quantitative photoacoustic imaging (qPAI) is to determine absolute chromophore concentrations from multispectral photoacoustic images. Achieving this goal would enable bias-free molecular photoacoustic imaging and the derivation of functional tissue biomarkers, such as local blood oxygenation, with numerous clinical implications. To deliver qPAI, two inverse problems must be solved: the acoustic inverse problem of reconstructing the initial pressure distribution from measured signals, and the optical inverse problem of reconstructing spatial images of optical absorption from the initial pressure. Unfortunately, these inverse problems are difficult to solve in practice. The validation of proposed qPAI algorithms is particularly challenging due to the lack of experimentally measured ground truth of the optical and acoustic tissue properties. With OpenQPAIData, we present a dataset of 30 tissue-mimicking phantoms imaged using three different photoacoustic systems: the Multispectral Optoacoustic Tomography (MSOT) InVision commercially produced system from iThera Medical GmbH, and the custom-built Transmission Reflection Optoacoustic and Ultrasound (TROPUS) and Spiral Volumetric Optoacoustic Tomography (SVOT) imaging systems developed by Prof. Daniel Razansky’s group. The dataset includes raw measurements, reconstructed images, manually segmented reference annotations, and matched optical property maps derived from double-integrating-sphere (DIS) measurements. By providing these multi-device imaging data with reference optical properties, we believe that OpenQPAIData enables the benchmarking of both acoustic and optical inverse solvers and supports the development of image quality assessment metrics for photoacoustic imaging.
GenMC addresses a critical barrier to quantitative PA imaging and offers a general strategy for rapid, high-fidelity approximation of light transport in tissue by enabling real-time, accurate, and reproducible quantification of tissue oxygenation.
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Photoacoustic tomography (PAT) couples optical absorption contrast with ultrasound resolution, but reconstructing the initial pressure distribution from sparse-view measurements is an ill-posed inverse problem. Iterative compressive-sensing solvers and unrolled deep networks both retain a dependence on the system m...
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Abstract. Significance Noninvasive characterization of periocular skin optical properties is critical for understanding tissue alterations associated with thyroid eye disease and other orbital adnexal pathologies. Spatial frequency domain imaging (SFDI) provides quantitative, in vivo assessment of tissue absorption and...
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Optical imaging is a major research tool in the basic sciences, but is limited by tissue scattering to short imaging depths. This prevents large-scale bio-imaging by allowing visualization of only the outer superficial layers of an organism, or specific components isolated from within the organism and prepared in-vitro...
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Photoacoustic (PA) and ultrasound (US) imaging provide complementary molecular, functional, and anatomical contrasts. Here, we present a panoramic PA-US imaging platform that integrates multispectral PA computed tomography (PACT) along with reflection-mode and transmission-mode US imaging through a single shared full-r...
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