Photoacoustic (PA) Imaging is an emerging biomedical imaging modality based on the laser-generated ultrasound. The method has unique advantages in providing microvessel structure visualization, neuroimaging, and functional imaging provided by its physical principle. Photoacoustic microscopy (PAM) is one of the PA imaging instruments which provides high resolution and contrast imaging of a near-field target. Relying on the acoustic focusing, Acoustic-resolution PAM (AR-PAM) is capable of reaching a sub-centimeter of penetration depth with sub-millimeter resolution and is optimized for tissue samples and small animals. However, the state-of-art AR-PAMs are large in size and expensive in cost, which hinders its democratization. There are previous researches conducted on reducing the cost by introducing a low-cost optical source or ultrasound acquisition device. Few research has investigated the possibility of modification on actuator design. The total system cost should be further reduced by substituting the translation stage while maintaining the imaging quality. In this research, a delta configuration actuation is introduced to the AR-PAM. The delta-configuration actuation adapted from a low-cost off-the-shelf 3D printer has been implemented in the design. An economical PAM system that integrates the combination of hardware and software enhancement is designed and tested in this research. With the software approach, advanced beamforming methods such as Delay-and-Sum with Coherence Factor (DAS+CF) and Delay-Multiply-and-Sum (DMAS) algorithms are applied to obtaining the high-resolution PA image through 3D reconstruction. The preliminary phantom study demonstrated the applicability of low-cost delta configuration actuators for AR-PAM imaging. The simulation study shows the beamforming algorithms has capability to remove the device precision error and increasing the tolerance. The research suggests that the 3D reconstruction algorithms significantly improve the resolution and contrast of the image quality.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-2386 |
| Date | 15 May 2020 |
| Creators | Gao, Shang |
| Contributors | Haichong Zhang, Advisor, Gregory S. Fischer, Committee Member, Loris Fichera, Committee Member |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
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