Mr. Zihao Li Profile

Zihao Li

at Nanchang Univ

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Author

Publications (11)

Proceedings Article | 14 November 2021 Paper

A novel 3D fusion method for the depth-of-field enhancement in optical-resolution photoacoustic microscopy based on cross bilateral filter algorithm

Bofang Chen, Sihang Li, Zhuangzhuang Wang, Chenghao Gu, Ziming Yu, Zihao Li, Xianlin Song

Proceedings Volume 11914, 119141E (2021) https://doi.org/10.1117/12.2612452

KEYWORDS: Image fusion, Photoacoustic spectroscopy, Photoacoustic microscopy, Image filtering, 3D image processing, Data fusion, Filtering (signal processing), 3D photoacoustic microscopy, Photoacoustic imaging, Optical filters

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Proceedings Article | 14 November 2021 Presentation

Digital high-speed compressed sensing photoacoustic imaging simulation platform based on K-Wave

Zihao Li, Xianlin Song, Aojie Zhao

Proceedings Volume 11914, 119141G (2021) https://doi.org/10.1117/12.2612457

KEYWORDS: Compressed sensing, Photoacoustic tomography, Photoacoustic spectroscopy, Virtual reality, Reconstruction algorithms, Photoacoustic imaging, MATLAB, Imaging technologies, Image resolution, Blood vessels

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Proceedings Article | 14 November 2021 Presentation + Paper

High-resolution 3D fusion method for optical-resolution photoacoustic microscopy using deep learning

Sihang Li, Zhuangzhuang Wang, Bofang Chen, Chenghao Gu, Ziming Yu, Zihao Li, Xianlin Song

Proceedings Volume 11914, 119140O (2021) https://doi.org/10.1117/12.2612466

KEYWORDS: Image fusion, Photoacoustic spectroscopy, Data fusion, 3D image processing, Photoacoustic microscopy, Image processing, 3D acquisition, Reconstruction algorithms, Information fusion, Convolutional neural networks

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Proceedings Article | 14 September 2021 Presentation + Paper

Compressed sensing photoacoustic tomography using Stagewise Weak OMP algorithm based on k-wave: a simulation study

Zihao Li, Aojie Zhao, Hongyu Zhang, Xianlin Song

Proceedings Volume 11875, 1187507 (2021) https://doi.org/10.1117/12.2600751

KEYWORDS: Reconstruction algorithms, Compressed sensing, Tissues, Photoacoustic tomography, Photoacoustic spectroscopy, Ultrasonics, Signal processing, Astatine, Signal detection, Image processing algorithms and systems

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Proceedings Article | 31 August 2021 Paper

Virtual platform of photoacoustic tomography based on K-Wave

Qianxiang Wan, Zihao Li, Hongyu Zhang, Shangkun Hou, Hao Zhou, Xianlin Song

Proceedings Volume 11907, 119073B (2021) https://doi.org/10.1117/12.2603840

KEYWORDS: Sensors, Photoacoustic spectroscopy, Photoacoustic imaging, Signal processing, Image processing, Ultrasonics, Photoacoustic tomography, Optical simulations, Signal to noise ratio

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Photoacoustic imaging is a biological non-destructive and non-invasive detection method based on the photoacoustic effect. It not only has the advantages of high optical imaging accuracy, high speed, and high contrast, but also has the advantages of good tissue penetration of ultrasound imaging. Early diagnosis of diseases, molecular optics, brain science and other fields have a wide range of applications. However, because the photoacoustic imaging technology is a multi-modal hybrid imaging technology, the research of this technology often requires expensive experimental equipment, and the experimental operation is complicated. Based on the K-Wave toolbox in Matlab, this paper builds a simulation platform for photoacoustic signals. Using this platform, successfully simulate the process of the ultrasonic signal emitted by the sample after absorbing the pulsed laser, and different numbers of sensors were used to collect the signal, and multiple sets of reconstructed images were obtained through back projection. By analyzing the relationship between the number of sensors and the reconstructed image and its signal-to-noise ratio and signal distribution, it is obtained that when the number of sensors is 50, the reconstructed image is clearer, the reconstructed signal distribution is closer to the original signal, and the signal-to-noise ratio is high. When the number of sensors gradually increased to 100, the reconstructed image, signal distribution, and signal-to-noise ratio did not change significantly, but the number of sensors doubled. Due to the high price of sensors, 50 to 100 sensors can be selected (or 50-100 angles can be scanned), which can reduce imaging time and cost while ensuring high imaging quality. Simulation platform of photoacoustic tomography base on K-Wave has the advantages of fast and convenient operation, and can complete the reconstruction of photoacoustic signals with high quality. From the relationship between the number of sensors and the signal distribution and signal-to-noise ratio of the reconstructed image, the influence of the number of sensors on the simulation effect can be obtained, which provides theoretical guidance for the application of photoacoustic imaging in biomedicine.

Proceedings Article | 18 June 2021 Paper

Optical and thermal interactions of different-wavelength ultrashort laser pulses with breast cancer based on COMSOL

Yuli Li, Ao Teng, Zihao Li, Xianlin Song

Proceedings Volume 11850, 1185007 (2021) https://doi.org/10.1117/12.2599023

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Proceedings Article | 12 April 2021 Paper

Blind deconvolution super-resolution photoacoustic microscope to achieve fine structural information of cerebral capillaries

Xianlin Song, Zihao Li, Jianshuang Wei

Proceedings Volume 11731, 1173107 (2021) https://doi.org/10.1117/12.2589658

KEYWORDS: Deconvolution, Photoacoustic spectroscopy, Capillaries, Image resolution, Tissues, Point spread functions, Photoacoustic imaging, Microscopes, Photoacoustic microscopy, Light scattering

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Photoacoustic imaging is becoming a very promising tool for the research of living organisms. It combines the high contrast of optical imaging and the high resolution of acoustic imaging to realize the imaging of absorption clusters in biological tissues. Since the scattering of ultrasound signals in biological tissues is 2-3 orders of magnitude weaker than the scattering of light in biological tissues, the endogenous absorption difference of tissues is directly used in the imaging process, so photoacoustic imaging has the advantages of deep imaging depth and non-destructive. As an important branch of photoacoustic imaging, photoacoustic microscopy can provide micron-level or even sub-micron-level imaging resolution, which is of great significance for biological research such as blood vessel detection. Since the lateral resolution of the photoacoustic microscopy imaging system depends on the focus of the laser, a higher resolution can be obtained by increasing the numerical aperture of the condenser objective. However, a large numerical aperture usually means a shorter working distance and makes the entire imaging system very sensitive to small optical defects. Therefore, the improvement of resolution through this method will be limited in practical applications. This paper implements a method of using iterative deconvolution to obtain a high-resolution photoacoustic image of the brain. The focal spot of the photoacoustic microscopy is measured to obtain the lateral PSF (point spread function) of the system. Making the measured PSF as the initial system PSF to perform Lucy- Richardson (LR) deconvolution. The image resolution of cerebral vasculature obtained by this method is higher. The full width at half maximum (FWHM) of width of the same cerebral capillaries before and after deconvolution are 7 μm and 3.6 μm, respectively, and the image definition is increased by about 1.9 times. Experiments show that this method can further improve the clarity of photoacoustic images of cerebral capillaries, which lays the foundation for further research on brain imaging.

Proceedings Article | 5 March 2021 Presentation + Paper

Spectrum analysis of photoacoustic signal based on COMSOL

Xianlin Song, Shuilong Wang, Xian Li, Ao Teng, Jianshuang Wei, Aojie Zhao, Bo Li, Zihao Li, Qiming He, Jinhong Zhang, Linfang Song

Proceedings Volume 11642, 116423S (2021) https://doi.org/10.1117/12.2589250

KEYWORDS: Photoacoustic spectroscopy, Spectrum analysis, Signal analyzers, Laser tissue interaction, Tumors, Light wave propagation, Light, Diffusion, Ultrasonics, Temperature metrology

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The study of the relationship between the spectral characteristics of the photoacoustic signal and the size, density and shape of the absorber is of great significance to image reconstruction and is of great practical significance to the better application of photoacoustic imaging in the medical field. This paper uses the simulation software COMSOL Multiphysics to design a two-dimensional simulation model based on finite element to study the relationship between the spectral characteristics of the photoacoustic signal and the properties of the absorber. In this study, the model consists of three parts: 1) water layer; 2) short pulse laser source (wavelength of 840nm); 3) gastric tumor tissue. The laser point source is located in the middle of the upper water layer. By solving the diffusion equation and the biological heat equation, respectively, the propagation of light in the water layer and the temperature change in biological tissues are simulated. When the absorber is irradiated by a Gaussian pulsed laser, due to the extremely short time, the absorber can be regarded as adiabatic expansion after absorbing energy, thereby generating ultrasonic waves. Using the finite element analysis method, the complex situation of photoacoustic imaging is transformed into the coupling of multiple physical fields, and the photoacoustic signal is obtained by numerical calculation of partial differential equations. Analyzing the simulation results, it is found that the spectral characteristics of the photoacoustic signal are closely related to the size of the absorber. The relationship obtained in this simulation experiment is: the spectral intercept and the size of the absorber have a power function relationship, the larger the size, the larger the spectral intercept , And the growth rate increases with the increase of the size; the spectral slope and the size of the absorber also have a power function relationship, the larger the size, the smaller the spectral slope, and the rate of change of the slope decreases with the increase of the size. For the relationship between the spectral characteristics and density of the photoacoustic signal, the intercept and slope characteristics are opposite. As the density of the photoacoustic absorber increases, the spectral slope of the photoacoustic signal increases, and the spectral intercept of the photoacoustic signal decreases. The photoacoustic signals and spectrograms of different shapes of absorbers have their own characteristics. The research results in this paper can promote the research of photoacoustic imaging and can better apply photoacoustic imaging in the medical field.

Proceedings Article | 5 March 2021 Presentation + Paper

Analysis on the photonic transmission and heat transfer of pulsed laser and breast cancer based on COMSOL multiphysics

Xianlin Song, Yuli Li, Ao Teng, Bo Li, Qiming He, Jinhong Zhang, Aojie Zhao, Zihao Li, Hao Chen, Jianshuang Wei, Lingfang Song, Cong Liu

Proceedings Volume 11622, 116220N (2021) https://doi.org/10.1117/12.2589051

KEYWORDS: Breast, Breast cancer, Tumors, Tumor growth modeling, Photoacoustic imaging, Mammary gland, Laser tissue interaction, Tissues, Oncology, Cancer

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Proceedings Article | 28 February 2021 Paper

Research on spectrum analysis of photoacoustic signal based on COMSOL platform

Xianlin Song, Shuilong Wang, Xian Li, Ao Teng, Zhouhua Chen, Jianshuang Wei, Aojie Zhao, Bo Li, Zihao Li, Qiming He, Jinhong Zhang, Lingfang Song

Proceedings Volume 11781, 117811O (2021) https://doi.org/10.1117/12.2591387

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The study of the relationship between the spectral characteristics of the photoacoustic signal and the shape and size of the absorber has important practical significance for image reconstruction. Using the commercial finite element simulation software COMSOL Multiphysics, a two-dimensional simulation model based on finite element was designed, which studied the relationship between the spectral characteristics of the photoacoustic signal and the shape and size of the absorber. In this study, the model consists of three parts: 1) water layer; 2) short pulse laser source (wavelength of 840nm); 3) gastric tumor tissue. The laser point source is located in the middle of the upper water layer. Simulate the propagation of light in the water layer by solving the diffusion equation. The temperature changes in biological tissues are obtained by solving the biothermal equation. When the absorber is irradiated by Gaussian pulses, due to the extremely short time, the absorber can be regarded as adiabatic expansion after absorbing energy, thereby generating ultrasonic waves. Using the finite element analysis method, the complex situation of photoacoustic imaging is transformed into the coupling of multiple physical fields and the numerical calculation of partial differential equations to obtain the photoacoustic signal. Fitting the simulation results shows that the spectral characteristics of the photoacoustic signal change regularly with the size of the absorber. The size of the absorber obtained in this paper has a power function relationship with the spectral intercept. The larger the size, the larger the spectral intercept, and the growth rate increases with the increase of the size. The size of the absorber and the spectral slope also have a power function relationship. The slope of the large spectrum is smaller, and the rate of change of the slope decreases as the size increases. At the same time, analyzing the photoacoustic spectrum of absorbers of different shapes also shows that absorbers of different shapes have their own characteristics. This research is helpful to understand the relationship between spectral characteristics and the shape and size of the absorber, and has certain theoretical guiding significance for image reconstruction.

Proceedings Article | 28 February 2021 Paper

Construction of breast cancer photoacoustic imaging model based on COMSOL

Xianlin Song, Yuli Li, Ao Teng, Zhipeng Zhang, Qiming He, Jinhong Zhang, Aojie Zhao, Bo Li, Zihao Li, Jianshuang Wei, Lingfang Song

Proceedings Volume 11781, 117810P (2021) https://doi.org/10.1117/12.2591388

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