Publications by authors named "Kangjun Guo"
Microscopic imaging techniques pursue high-resolution, large depth of field (DoF) imaging but are limited by hardware, especially the strong focusing of objective lenses. Optical-resolution photoacoustic microscopy (OR-PAM) has a narrow DoF due to the intense laser focusing needed for high-resolution imaging. To address this, we propose a novel volumetric information fusion method using a three-dimensional siamese multi-level features convolutional neural network (3DSMFCNN) for cost-effective, large-DoF imaging.
View Article and Find Full Text PDFAs a novel non-invasive hybrid biomedical imaging technology, photoacoustic tomography combines the advantages of high contrast of optical imaging and high penetration of acoustic imaging. However, the conventional standard reconstruction methods under sparse view may lead to low-quality image in photoacoustic tomography. To address this problem, an advanced sparse reconstruction method for photoacoustic tomography based on the mean-reverting diffusion model is proposed.
View Article and Find Full Text PDFArticle Synopsis
- Photoacoustic tomography (PAT) is a cutting-edge imaging technique that creates high-resolution images of biological tissues, but often struggles with artifact issues in limited-view scenarios.
- This study introduces a new reconstruction strategy that uses multiple diffusion models and alternating iteration methods to fill in missing data, which leads to improved image quality and stability.
- When tested on a dataset with only 60° views, the method showed a significant increase in image clarity with improvements in peak signal-to-noise ratio and structural similarity, indicating a promising advancement for clinical applications of PAT.
Photoacoustic tomography (PAT) regularly operates in limited-view cases owing to data acquisition limitations. The results using traditional methods in limited-view PAT exhibit distortions and numerous artifacts. Here, a novel limited-view PAT reconstruction strategy that combines model-based iteration with score-based generative model was proposed.
View Article and Find Full Text PDFSparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration.
Photoacoustics
October 2023
Article Synopsis
- Photoacoustic tomography combines optical and acoustic imaging for better clarity and depth but faces quality issues with standard reconstruction methods under sparse views.
- A new model-based reconstruction method using a score-based diffusion model was developed to enhance image quality by incorporating prior information as a constraint in the reconstruction process.
- Test results showed that this method significantly outperforms traditional techniques, particularly under extreme sparse conditions, improving image clarity and potentially reducing both acquisition time and costs in photoacoustic imaging.
Multifactor effects on the NO emissions and yield of potato fields based on the DNDC model.
Environ Sci Pollut Res Int
April 2022
Maintaining or increasing grain yields while also reducing the emissions of field agricultural greenhouse gases is an important objective. To explore the multifactor effects of nitrogen fertilizer on nitrous oxide (NO) emissions and the yield of potato fields and to verify the applicability of the denitrification-decomposition (DNDC) model when used to project the NO emission load and yield, this research chooses a potato field in Shenyang northeast China from 2017 to 2019 as the experiment site. The experiment includes four nitrogen levels observing the emission of NO by static chamber/gas chromatograph techniques.
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