Mr. Hongzhi Zuo Profile

Hongzhi Zuo

at Tsinghua Univ

SPIE Involvement:

Author

Publications (5)

Proceedings Article | 18 December 2023 Paper

passFormer: heterogeneous feature-aware CNN-transformer coupling network for sparse sampling photoacoustic tomography

Yize Gao, Hongzhi Zuo, Cheng Ma, Liujie Gu

Proceedings Volume 12967, 129670H (2023) https://doi.org/10.1117/12.3008548

KEYWORDS: Image restoration, Photoacoustic tomography, Aliasing, In vivo imaging, Feature extraction

Read Abstract +

Photoacoustic imaging (PAI) is an emerging modality that has generated increasing interest for its uses in clinical research and translation. To fully exploit its potential for various preclinical and clinical applications, it is necessary to develop systems that offer high imaging speed, reasonable cost, and manageable data flow. Currently, a significant challenge lies in the fabrication of ultrasound arrays, as many of them are not densely populated enough to fully sample the signals. Ideally, the pitch of the arrays should be half of the center ultrasonic wavelength to prevent spatial undersampling and the subsequent reconstruction artifacts, such as aliasing artifacts and structural deformation. Here, a novel photoacoustic sparse sampling Transformer-CNN coupling network (passFormer) is proposed to decouple target details and spatial under-sampling artifacts from high-frequency image information in a heterogeneous feature-aware manner. To be specific, we first decompose the sparse sampling (SS) photoacoustic (PA) images into 2 parts: high-frequency (HF) and low-frequency (LF) compositions. Our methodology incorporates two bridging modules, the LF modules and the HF modules. The LF coupling module extracts content features (X_c) and latent texture feature (X_tex), and the HF coupling module extracts high-frequency embedding (X_emb) containing the target details features (X_detail) and under-sampling artifacts (X_art). We feed X_t and X_emb into a modified transformer with three encoders and decoders to obtain well-refined HF texture features. At last, we combine the refined HF texture features with pre-extracted X_c by pixel-wise summation reconstruction. Experimental results on publicly available full and sparse reconstruction datasets of mouse and phantom PA images highlight the superior performance of our method, particularly in live mouse imaging. This new approach enables accelerated data acquisition and image reconstruction, facilitating the development of practical and cost-effective imaging systems.

SPIE Journal Paper | 1 July 2022 Open Access

Multi-segmented feature coupling for jointly reconstructing initial pressure and speed of sound in photoacoustic computed tomography

Kexin Deng, Xuanhao Wang, Chuangjian Cai, Manxiu Cui, Hongzhi Zuo, Jianwen Luo, Cheng Ma

JBO, Vol. 27, Issue 07, 076001, (July 2022) https://doi.org/10.1117/12.10.1117/1.JBO.27.7.076001

KEYWORDS: Photoacoustic tomography, Image quality, Tissues, Signal detection, Ultrasonography, Image processing, Reconstruction algorithms, Image restoration, Animals, Correlation coefficients

Read Abstract +

DOWNLOAD PAPER

Proceedings Article | 9 October 2021 Poster + Paper

A spectral-domain model-based method for simultaneous oxygen saturation quantification and contrast agent identification

Hongzhi Zuo, Manxiu Cui, Bangyan Wang, Cheng Ma

Proceedings Volume 11900, 1190036 (2021) https://doi.org/10.1117/12.2602598

KEYWORDS: Photoacoustic spectroscopy, Blood oxygen saturation, Tissue optics, Absorption, Scattering, Multispectral imaging, Light scattering

Read Abstract +

Proceedings Article | 10 October 2020 Presentation

Photoacoustic computed tomography with adaptive wavefront correction

Kexin Deng, Manxiu Cui, Hongzhi Zuo, Xuanhao Wang, Cheng Ma

Proceedings Volume 11553, 115530M (2020) https://doi.org/10.1117/12.2574945

KEYWORDS: Photoacoustic tomography, Wavefronts, Wavefront distortions, Ultrasonography, Tissues, Adaptive optics, Image quality, Deep tissue imaging, Photoacoustic spectroscopy, Light scattering

Proceedings Article | 10 October 2020 Presentation

A convex cone method for accurate blood oxygenation photoacoustic imaging

Bangyan Wang, Hongzhi Zuo, Cheng Ma, Xuanhao Wang, Manxiu Cui

Proceedings Volume 11550, 1155006 (2020) https://doi.org/10.1117/12.2574835

KEYWORDS: Photoacoustic imaging, Blood, Tissue optics, Blood oxygen saturation, In vivo imaging, Data modeling, Multispectral imaging, Diffusion, Biological research, Monte Carlo methods

Read Abstract +

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years