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Your search keyword '"Zhuangzhuang Tong"' showing total 3 results
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3 results on '"Zhuangzhuang Tong"'

1. Photoacoustic/ultrasonic dual-mode imaging for monitoring angiogenesis and synovial erosion in rheumatoid arthritis

Author

Zhen Wang, Zhuangzhuang Tong, Hongjiang Chen, Guangshuai Nie, Jia Hu, Weiyang Liu, Erqi Wang, Bo Yuan, Zhiyang Wang, and Jun Hu

Subjects
Photoacoustic imaging, Ultrasonic imaging, Rheumatoid arthritis, Angiogenesis, Physics, QC1-999, Acoustics. Sound, QC221-246, Optics. Light, QC350-467
Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the formation of new vessels, synovial proliferation and destruction of articular cartilage. However, characteristic early diagnostic and therapeutic monitoring methods are still lacking. We report a study using a photoacoustic/ultrasound (PA/US) dual-mode imaging for RA disease. By establishing a collagen-induced (CIA) RA mouse model to classify disease states based on a subjective grading system, PA/US imaging allows real-time assessment of synovial erosion and vascular opacification within the knee joint in different disease states at high spatial resolution. The system also quantitatively monitors subcutaneous vascular physiology and morphology in the hind paw of mice, measuring the area and photoacoustic signal intensity of vascular proliferation and showing a positive correlation with disease grading. Compared to traditional subjective scoring of arthritis severity, the PA/US imaging is more sensitive i.e., vascular signals and synovial erosion can be observed early in the course of arthritis.

Published
2023
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3. High‐security photoacoustic identity recognition by capturing hierarchical vascular structure of finger

Author

Sihua Yang, Mingman Sun, Zhuangzhuang Tong, Zhiyang Wang, Wuyu Zhang, and Yuanzheng Ma

Subjects
High security, Biometrics, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, General Physics and Astronomy, Photoacoustic imaging in biomedicine, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, Fingers, 010309 optics, Wavelet, Fingerprint, 0103 physical sciences, Feature (machine learning), General Materials Science, Identity Recognition, business.industry, Spectrum Analysis, 010401 analytical chemistry, General Engineering, Feature recognition, Pattern recognition, General Chemistry, Identity recognition, 0104 chemical sciences, Biometric Identification, Artificial intelligence, business, Algorithms
Abstract

Currently, most biometric methods mainly use single features, making them easily forged and cracked. In this study, a novel triple-layers biometric recognition method, based on photoacoustic microscopy, is proposed to improve the security of biometric identity recognition. Using the photoacoustic (PA) dermoscope, three-dimensional absorption-structure information of the fingers was obtained. Then, by combining U-Net, Gabor filtering, wavelet analysis and morphological transform, a lightweight algorithm called photoacoustic depth feature recognition algorithm (PADFR) was developed to automatically realize stratification (the fingerprint, blood vessel fingerprint and venous vascular), extracting feature points and identity recognition. The experimental results show that PADFR can automatically recognize the PA hierarchical features with an average accuracy equal to 92.99%. The proposed method is expected to be widely used in biometric identification system due to its high security. This article is protected by copyright. All rights reserved.

Published
2021
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