Paper
19 February 2018 Photoacoustic imaging optimization with raw signal deconvolution and empirical mode decomposition
Author Affiliations +
Abstract
Photoacoustic (PA) signal of an ideal optical absorb particle is a single N-shape wave. PA signals of a complicated biological tissue can be considered as the combination of individual N-shape waves. However, the N-shape wave basis not only complicates the subsequent work, but also results in aliasing between adjacent micro-structures, which deteriorates the quality of the final PA images. In this paper, we propose a method to improve PA image quality through signal processing method directly working on raw signals, which including deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent point spread function (PSF) which is measured in advance. Then, EMD is adopted to adaptively re-shape the PA signals with two constraints, positive polarity and spectrum consistence. With our proposed method, the built PA images can yield more detail structural information. Micro-structures are clearly separated and revealed. To validate the effectiveness of this method, we present numerical simulations and phantom studies consist of a densely distributed point sources model and a blood vessel model. In the future, our study might hold the potential for clinical PA imaging as it can help to distinguish micro-structures from the optimized images and even measure the size of objects from deconvolved signals.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chengwen Guo, Jing Wang, Yu Qin, Hongchen Zhan, Jie Yuan, Qian Cheng, and Xueding Wang "Photoacoustic imaging optimization with raw signal deconvolution and empirical mode decomposition", Proc. SPIE 10494, Photons Plus Ultrasound: Imaging and Sensing 2018, 1049451 (19 February 2018); https://doi.org/10.1117/12.2286411
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Cited by 2 scholarly publications.
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KEYWORDS
Deconvolution

Signal processing

Signal detection

Image quality

Transducers

Photoacoustic imaging

Tissue optics

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