18 March 2016 Reflection-artifact-free photoacoustic imaging using PAFUSion (photoacoustic-guided focused ultrasound)
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Abstract
Reflection artifacts caused by acoustic inhomogeneities are a main challenge to deep-tissue photoacoustic imaging. Photoacoustic transients generated by the skin surface and superficial vasculature will propagate into the tissue and reflect back from echogenic structures to generate reflection artifacts. These artifacts can cause problems in image interpretation and limit imaging depth. In its basic version, PAFUSion mimics the inward travelling wave-field from blood vessel-like PA sources by applying focused ultrasound pulses, and thus provides a way to identify reflection artifacts. In this work, we demonstrate reflection artifact correction in addition to identification, towards obtaining an artifact-free photoacoustic image. In view of clinical applications, we implemented an improved version of PAFUSion in which photoacoustic data is backpropagated to imitate the inward travelling wave-field and thus the reflection artifacts of a more arbitrary distribution of PA sources that also includes the skin melanin layer. The backpropagation is performed in a synthetic way based on the pulse-echo acquisitions after transmission on each single element of the transducer array. We present a phantom experiment and initial in vivo measurements on human volunteers where we demonstrate significant reflection artifact reduction using our technique. The results provide a direct confirmation that reflection artifacts are prominent in clinical epi-photoacoustic imaging, and that PAFUSion can reduce these artifacts significantly to improve the deep-tissue photoacoustic imaging.
Conference Presentation
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Mithun Kuniyil Ajith Singh, Mithun Kuniyil Ajith Singh, Michael Jaeger, Michael Jaeger, Martin Frenz, Martin Frenz, Wiendelt Steenbergen, Wiendelt Steenbergen, "Reflection-artifact-free photoacoustic imaging using PAFUSion (photoacoustic-guided focused ultrasound)", Proc. SPIE 9708, Photons Plus Ultrasound: Imaging and Sensing 2016, 97081R (18 March 2016); doi: 10.1117/12.2212775; https://doi.org/10.1117/12.2212775
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