Full-frequency correction of spatial impulse response in back-projection scheme using space-variant filtering for optoacoustic mesoscopy

Lü, Tong; Wang, Yihan; Li, Jiao; Prakash, Jaya; Gao, Feng; Ntziachristos, Vasilis

doi:10.1016/j.pacs.2020.100193

Cited by 9 publications

(5 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The SD σ was determined by σ = 0 . 03 m a x [ û e ] , where m a x [ û e ] is the maximal component of the theoretical sampling voltage vector without noise. 12 The SIR vector from the detector position to each location in the imaging domain was generated using the Field II simulation toolbox of MATLAB, 58 and the EIR was obtained by referring to Sheng et al 32 as shown in Figure 3.…”

Section: Methodsmentioning

confidence: 99%

“…max[ ] û e , where max[ ] û e is the maximal component of the theoretical sampling voltage vector without noise. 12 The SIR vector from the detector position to each location in the imaging domain was generated using the Field II simulation toolbox of MATLAB, 58 and the EIR was obtained by referring to Sheng et al 32 as shown in Figure 3. In addition to visual inspection, we also quantitatively evaluated the quality of reconstructed images using standard metrics, including peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and normalized mean square absolute distance (NMSAD).…”

Section: Reconstruction Of Images Representing Aoedmentioning

confidence: 99%

See 1 more Smart Citation

Image reconstruction for endoscopic photoacoustic tomography including effects of detector responses

Sun

2022

Exp Biol Med (Maywood)

View full text Add to dashboard Cite

In photoacoustic tomography (PAT), conventional image reconstruction methods are generally based on the assumption of an ideal point-like ultrasonic detector. This assumption is appropriate when the receiving surface of the detector is sufficiently small and/or the distance between the imaged object and the detector is large enough. However, it does not hold in endoscopic applications of PAT. In this study, we propose a model-based image reconstruction method for endoscopic photoacoustic tomography (EPAT), considering the effect of detector responses on image quality. We construct a forward model to physically describe the imaging process of EPAT, including the generation of the initial pressure due to optical absorption and thermoelastic expansion, the propagation of photoacoustic waves in tissues, and the acoustic measurement. The model outputs the theoretical sampling voltage signal, which is the response of the ultrasonic detector to the acoustic pressure reaching its receiving surface. The images representing the distribution map of the optical absorption energy density on cross-sections of the imaged luminal structures are reconstructed from the sampling voltage signals output by the detector through iterative inversion of the forward model. Compared with the conventional approaches based on back-projection and other imaging models, our method improved the quality and spatial resolution of the resulting images.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Reconstruction Of Images Representing Aoedmentioning

confidence: 99%

Image reconstruction for endoscopic photoacoustic tomography including effects of detector responses

Sun

2022

Exp Biol Med (Maywood)

View full text Add to dashboard Cite

show abstract

“…By setting parameters such as the region of interest (ROI), sampling frequency, and transducer shape, the PSF solution within the ROI can be obtained. Lu et al [93] incorporated the obtained PSF solution as a filtering mechanism into the BP algorithm to effectively correct the PA signals, then eliminated the influence of the SIR.…”

Section: Compression Sensingmentioning

confidence: 99%

End-to-End Algorithm Research in PACT—From Signal Processing to Reconstruction Solution to Image Processing

Liu,

Gao,

Cheng

et al. 2024

Preprint

View full text Add to dashboard Cite

Photoacoustic computed tomography (PACT) is an innovative biomedical imaging technique that has gained significant application in the field of biomedicine due to its ability to visualize optical contrast with high resolution and deep tissue penetration. However, the inherent challenges associated with photoacoustic signal excitation, propagation and detection often result in suboptimal image quality. To overcome these limitations, researchers have developed various advanced algorithms that span the entire image reconstruction pipeline. This review paper aims to presents a detailed analysis of the latest advancements in PACT algorithms and synthesizes these algorithms into a coherent framework. We provide a tripartite analysis—from signal processing to reconstruction solution to image processing, covering a spectrum of techniques. The principles and methodologies, as well as their applicability and limitations, are thoroughly discussed. The primary objective of this study is to provide a thorough review of advanced algorithms applicable to PACT, offering both theoretical foundations and practical guidance for enhancing the imaging effect of PACT.

show abstract

“…To our knowledge, there have been some researches that adopt deconvolution methods to improve the performance of PAT system. For example, some of them deconvolve the recorded PA signals with either spatial impulse response (SIR) [32] , [33] or electrical impulse response (EIR) [34] , [35] to enhance the resolution. In [36] , [37] , the authors propose a deconvolution based reconstruction method, which models the recorded signals as the convolution of the optical absorption map and the impulse response of the PAT system.…”

Section: Introductionmentioning

confidence: 99%

Image restoration for ring-array photoacoustic tomography system based on blind spatially rotational deconvolution

Dong,

Zhu,

Xie

et al. 2024

Photoacoustics

View full text Add to dashboard Cite

Full-frequency correction of spatial impulse response in back-projection scheme using space-variant filtering for optoacoustic mesoscopy

Cited by 9 publications

References 41 publications

Image reconstruction for endoscopic photoacoustic tomography including effects of detector responses

Image reconstruction for endoscopic photoacoustic tomography including effects of detector responses

End-to-End Algorithm Research in PACT—From Signal Processing to Reconstruction Solution to Image Processing

Image restoration for ring-array photoacoustic tomography system based on blind spatially rotational deconvolution

Contact Info

Product

Resources

About