1. Generalized spatial coherence reconstruction for photoacoustic computed tomography
- Author
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Nikhila Nyayapathi, Jun Xia, Jorge Tordera Mora, Xiaohua Feng, and Liang Gao
- Subjects
Paper ,Beamforming ,Computer science ,Biomedical Engineering ,Iterative reconstruction ,photoacoustic tomography ,01 natural sciences ,Signal ,Imaging ,010309 optics ,Biomaterials ,Signal-to-noise ratio ,0103 physical sciences ,Image Processing, Computer-Assisted ,Computer Simulation ,Image resolution ,Ultrasonography ,Phantoms, Imaging ,Noise (signal processing) ,Reconstruction algorithm ,Coherence (statistics) ,Atomic and Molecular Physics, and Optics ,Electronic, Optical and Magnetic Materials ,spatial coherence ,beamformer ,Tomography, X-Ray Computed ,Algorithm ,Algorithms - Abstract
Significance: Coherence, a fundamental property of waves and fields, plays a key role in photoacoustic image reconstruction. Previously, techniques such as short-lag spatial coherence (SLSC) and filtered delay, multiply, and sum (FDMAS) have utilized spatial coherence to improve the reconstructed resolution and contrast with respect to delay-and-sum (DAS). While SLSC uses spatial coherence directly as the imaging contrast, FDMAS employs spatial coherence implicitly. Despite being more robust against noise, both techniques have their own drawbacks: SLSC does not preserve a relative signal magnitude, and FDMAS shows a reduced contrast-to-noise ratio. Aim: To overcome these limitations, our aim is to develop a beamforming algorithm—generalized spatial coherence (GSC)—that unifies SLSC and FDMAS into a single equation and outperforms both beamformers. Approach: We demonstrated the application of GSC in photoacoustic computed tomography (PACT) through simulation and experiments and compared it to previous beamformers: DAS, FDMAS, and SLSC. Results: GSC outperforms the imaging metrics of previous state-of-the-art coherence-based beamformers in both simulation and experiments. Conclusions: GSC is an innovative reconstruction algorithm for PACT, which combines the strengths of FDMAS and SLSC expanding PACT’s applications.
- Published
- 2021