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2,889 results on '"Song, Qiang"'

1. Phase space framework enables a variable-scale diffraction model for coherent imaging and display

Author

Li, Zhi, Luo, Xuhao, Wang, Jing, Yuan, Xin, Teng, Dongdong, Song, Qiang, and Duan, Huigao

Subjects
Physics - Applied Physics, Physics - Optics
Abstract

The fast algorithms in Fourier optics have invigorated multifunctional device design and advanced imaging technologies. However, the necessity for fast computations has led to limitations in the widely used conventional Fourier methods, manifesting as fixed size image plane at a certain diffraction distance. These limitations pose challenges in intricate scaling transformations, 3D reconstructions and full-color displays. Currently, there is a lack of effective solutions, often resorting to pre-processing that compromise fidelity. In this paper, leveraging a higher-dimensional phase space method, we present a universal framework allowing for customized diffraction calculation methods. Within this framework, we establish a variable-scale diffraction computation model which allows the adjustment of the size of the image plane and can be operated by fast algorithms. We validate the model's robust variable-scale capabilities and its aberration automatic correction capability for full-color holography, achieving high fidelity. The large-magnification tomography experiment demonstrates that this model provides a superior solution for holographic 3D reconstruction. In addition, this model is applied to achieve full-color metasurface holography with near-zero crosstalk, showcasing its versatile applicability at nanoscale. Our model presents significant prospects for applications in the optics community, such as beam shaping, computer-generated holograms (CGHs), augmented reality (AR), metasurface optical elements (MOEs) and advanced holographic head-up display (HUD) systems., Comment: 26 pages, 13 figures

Published
2024

6. B-Spine: Learning B-Spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

Author

Wang, Hao, Song, Qiang, Yin, Ruofeng, Ma, Rui, Yu, Yizhou, and Chang, Yi

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Spinal curvature estimation is important to the diagnosis and treatment of the scoliosis. Existing methods face several issues such as the need of expensive annotations on the vertebral landmarks and being sensitive to the image quality. It is challenging to achieve robust estimation and obtain interpretable results, especially for low-quality images which are blurry and hazy. In this paper, we propose B-Spine, a novel deep learning pipeline to learn B-spline curve representation of the spine and estimate the Cobb angles for spinal curvature estimation from low-quality X-ray images. Given a low-quality input, a novel SegRefine network which employs the unpaired image-to-image translation is proposed to generate a high quality spine mask from the initial segmentation result. Next, a novel mask-based B-spline prediction model is proposed to predict the B-spline curve for the spine centerline. Finally, the Cobb angles are estimated by a hybrid approach which combines the curve slope analysis and a curve-based regression model. We conduct quantitative and qualitative comparisons with the representative and SOTA learning-based methods on the public AASCE2019 dataset and our new proposed CJUH-JLU dataset which contains more challenging low-quality images. The superior performance on both datasets shows our method can achieve both robustness and interpretability for spinal curvature estimation.

Published
2023

7. Targeting DKK1 enhances the antitumor activity of paclitaxel and alleviates chemotherapy-induced peripheral neuropathy in breast cancer

Author

Hong-Xiang Shi, Hang-Tian Tao, Jin-Jin He, Feng-Yi Zhu, Cui-Qing Xie, Yu-Na Cheng, Li-Li Hou, Hua Sun, Chang-Jiang Qin, Dong Fang, and Song-Qiang Xie

Subjects
Paclitaxel, DKK1, EGFR, Peripheral neuropathy, Breast cancer, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Chemotherapy in combination with immunotherapy has gradually shown substantial promise to increase T cell infiltration and antitumor efficacy. However, paclitaxel in combination with immune checkpoint inhibitor targeting PD-1/PD-L1 was only used to treat a small proportion of metastatic triple-negative breast cancer (TNBC), and the clinical outcomes was very limited. In addition, this regimen cannot prevent paclitaxel-induced peripheral neuropathy. Therefore, there was an urgent need for a novel target to enhance the antitumor activity of paclitaxel and alleviate chemotherapy-induced peripheral neuropathy in breast cancer. Here, we found that Dickkopf-1 (DKK1) expression was upregulated in multiply subtypes of human breast cancer specimens after paclitaxel-based chemotherapy. Mechanistic studies revealed that paclitaxel promoted DKK1 expression by inducing EGFR signaling in breast cancer cells, and the upregulation of DKK1 could hinder the therapeutic efficacy of paclitaxel by suppressing the infiltration and activity of CD8+ T cells in tumor microenvironment. Moreover, paclitaxel treatment in tumor-bearing mice also increased DKK1 expression through the activation of EGFR signaling in the primary sensory dorsal root ganglion (DRG) neurons, leading to the development of peripheral neuropathy, which is charactered by myelin damage in the sciatic nerve, neuropathic pain, and loss of cutaneous innervation in hindpaw skin. The addition of an anti-DKK1 antibody not only improved therapeutic efficacy of paclitaxel in two murine subtype models of breast cancer but also alleviated paclitaxel-induced peripheral neuropathy. Taken together, our findings providing a potential chemoimmunotherapy strategy with low neurotoxicity that can benefit multiple subtypes of breast cancer patients.

Published
2024
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