Biomedical Photoacoustic Imaging Optimization with Deconvolution and EMD Reconstruction

Guo, Chengwen; Chen, Yingna; Yuan, Jie; Zhu, Yunhao; Cheng, Qian; Wang, Xueding

doi:10.3390/app8112113

Cited by 11 publications

(10 citation statements)

References 18 publications

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“…Since SATV and SAFPDE regularizations have complementary merits in image restoration, it is appealing to combine the two filters together. Motivated by the combination strategy proposed in [36], we develop an RLBD algorithm with hybrid reweighted adap-tive total variation (RLBD-HRATV) that uses a weighting function (defined in Equations (18) and (19)) to update the weight of SATV and SAFPDE in a pixel-wise manner at each iteration. To avoid ambiguity, we denote the solution u(x) in Equations ( 12) and ( 15) as f (x) and g(x), respectively.…”

Section: Hybrid Reweighted Adaptive Total Variation (Hratv)mentioning

confidence: 99%

“…Wiener filter deconvolution has also been studied in optoacoustic imaging to restore the initial wideband signals [16][17][18]. More recently, Guo proposed a Wiener filter with empirical mode decomposition (EMD) in linear array based OAT to improve the axial resolution and reduce unexpected artifacts [19]. A deconvolution method with Tikhonov regularization has also been presented to correct the optoacoustic signal based on the impulse response of the transducer [20,21].…”

Section: Introductionmentioning

confidence: 99%

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Image Deconvolution with Hybrid Reweighted Adaptive Total Variation (HRATV) for Optoacoustic Tomography

et al. 2021

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Optoacoustic tomography (OAT) is a hybrid biomedical imaging modality that usually employs a transducer array to detect laser-generated ultrasonic signals. The reconstructed image suffers low contrast and degraded resolution due to the limited bandwidth and the spatial directivity of the transducer element. Here, we introduce a modified image deconvolution method with a hybrid reweighted adaptive total variation tailored to improve the image quality of OAT. The effectiveness and the parameter dependency of the proposed method are verified on standard test images. The performance of the proposed method in OAT is then characterized on both simulated phantoms and in vivo mice experiments, which demonstrates that the modified deconvolution algorithm is able to restore the sharp edges and fine details in OAT simultaneously. The signal-to-noise ratios (SNRs) of the target structures in mouse liver and brain were improved by 4.90 and 12.69 dB, respectively. We also investigated the feasibility of using Fourier ring correlation (FRC) as an indicator of the image quality to monitor the deconvolution progress in OAT. Based on the experimental results, a practical guide for image deconvolution in OAT was summarized. We anticipate that the proposed method will be a promising post-processing tool to enhance the visualization of micro-structures in OAT.

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Section: Hybrid Reweighted Adaptive Total Variation (Hratv)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Image Deconvolution with Hybrid Reweighted Adaptive Total Variation (HRATV) for Optoacoustic Tomography

et al. 2021

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“…Optimization‐based methods can fully consider the characteristics of the detector in the system matrix thus are potentially capable of restoring the degraded lateral resolution, but the algebraical inversion of its system matrix generally involves enormous computational cost, 20,23,24,30‐35 which hinders its application in high‐resolution and 3D image reconstructions. Image post‐processing methods such as deconvolution can also improve the lateral resolution, but it can cause strong image noise or introduce some artifacts 36‐38 . Therefore, there is still an urgent need for developing new PAT reconstruction algorithms to overcome the effect of finite aperture in circular‐scanning‐based PAT.…”

Section: Introductionmentioning

confidence: 99%

Approximate back‐projection method for improving lateral resolution in circular‐scanning‐based photoacoustic tomography

Wang

et al. 2021

Medical Physics

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Purpose In circular‐scanning‐based photoacoustic tomography (PAT), the effect of finite transducer aperture has not been effectively resolved. The goal of this paper is to propose a practical reconstruction method that accounts for the finite transducer aperture to improve the lateral resolution. Methods We for the first time propose to calculate the spatial‐temporal response (STR) of the employed finite‐sized transducer in a forward model, and then compensate the time delay and the directional sensitivity of the transducer in the framework of the back‐projection method. Both simulation and phantom experiments were carried out to evaluate the lateral resolution improvement with the proposed method. The performance of this new method for imaging complicated targets was also assessed by calculating the mean image gradient. Results Simulation results showed that with this new method the lateral resolution for off‐center targets can be as good as that for the center targets. Phantom experimental results showed that this new method can improve the lateral resolution more than two times for a point target about 5 mm far from the rotation center. Phantom experimental results also showed that many blurred fine structures of a piece of leaf veins at the off‐center regions were well restored with the new method, and the mean image gradient improved about 1.3 times. Conclusion The proposed new method can effectively account for the effect of finite transducer aperture for circular‐scanning‐based PAT in homogenous acoustic media. This new method also features its robustness and computational efficiency, so that it is a worthy replacement to the conventional back‐projection algorithm in circular‐scanning‐based PAT. This new method can be of great importance to the design of circular‐scanning or spherical‐scanning‐based PAT systems.

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“…On the other hand, their application areas are expanding and deepening gradually. EMD has been widely used in different fields, such as short-term wind speed forecasting combined with hybrid linear and nonlinear models [8], the detection and location of pipeline leakage [9], the detection of incipient damages for truss structures [10], denoising for grain flow signal [11], biomedical photoacoustic imaging optimization [12] and heart rate variability analysis [13]. Many scholars have also applied EEMD to their research fields, such as wind speed forecasting combined with the cuckoo search algorithm [14], machine feature extraction combined with a kernel-independent component [15], feature extraction for motor bearing combined with multi-scale fuzzy entropy [16], a bearing fault diagnosis combined with correlation coefficient analysis [17], a partial discharge feature extraction combined with sample entropy [18] and monthly streamflow forecasting combined with multi-scale predictors selection [19].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Energy Feature Extraction Approach for Ship-Radiated Noise Based on CEEMDAN Combined with Energy Difference and Energy Entropy

Chen

2019

Processes

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Influenced by the complexity of ocean environmental noise and the time-varying of underwater acoustic channels, feature extraction of underwater acoustic signals has always been a difficult challenge. To solve this dilemma, this paper introduces a hybrid energy feature extraction approach for ship-radiated noise (S-RN) based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) combined with energy difference (ED) and energy entropy (EE). This approach, named CEEMDAN-ED-EE, has two main advantages: (i) compared with empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN has better decomposition performance by overcoming mode mixing, and the intrinsic mode function (IMF) obtained by CEEMDAN is beneficial to feature extraction; (ii) the classification performance of the single energy feature has some limitations, nevertheless, the proposed hybrid energy feature extraction approach has a better classification performance. In this paper, we first decompose three types of S-RN into sub-signals, named intrinsic mode functions (IMFs). Then, we obtain the features of energy difference and energy entropy based on IMFs, named CEEMDAN-ED and CEEMDAN-EE, respectively. Finally, we compare the recognition rate for three sorts of S-RN by using the following three energy feature extraction approaches, which are CEEMDAN-ED, CEEMDAN-EE and CEEMDAN-ED-EE. The experimental results prove the effectivity and the high recognition rate of the proposed approach.

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Biomedical Photoacoustic Imaging Optimization with Deconvolution and EMD Reconstruction

Cited by 11 publications

References 18 publications

Image Deconvolution with Hybrid Reweighted Adaptive Total Variation (HRATV) for Optoacoustic Tomography

Image Deconvolution with Hybrid Reweighted Adaptive Total Variation (HRATV) for Optoacoustic Tomography

Approximate back‐projection method for improving lateral resolution in circular‐scanning‐based photoacoustic tomography

A Hybrid Energy Feature Extraction Approach for Ship-Radiated Noise Based on CEEMDAN Combined with Energy Difference and Energy Entropy

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