Mr. Hui Zeng Profile

Hui Zeng

at Southern Medical Univ

SPIE Involvement:

Author

Publications (4)

Proceedings Article | 7 April 2023 Poster + Paper

Multi-view based computer-aided model with anatomical position prior for architectural distortion detection in digital breast tomosynthesis

Xiangyuan Ma, Zilong He, Yue Li, Weixiong Zeng, Jiawei Pan, Jialing Liu, Weimin Xu, Zeyuan Xu, Sina Wang, Chanjuan Wen, Hui Zeng, Jiefeng Wu, Zhaodong Zeng, Weiguo Chen, Yao Lu

Proceedings Volume 12465, 124652V (2023) https://doi.org/10.1117/12.2654418

KEYWORDS: Digital breast tomosynthesis, Computer aided detection, Breast, 3D modeling, Cancer detection, Architectural distortion, Medical image processing

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Proceedings Article | 4 April 2022 Presentation + Paper

Computer-aided detection for architectural distortion: a comparison of digital breast tomosynthesis and digital mammography

Yue Li, Zilong He, Xiangyuan Ma, Weixiong Zeng, Jialing Liu, Weimin Xu, Zeyuan Xu, Sina Wang, Chanjuan Wen, Hui Zeng, Jiefang Wu, Weiguo Chen, Yao Lu

Proceedings Volume 12033, 120330W (2022) https://doi.org/10.1117/12.2611287

KEYWORDS: Digital breast tomosynthesis, Digital mammography, Computer-aided diagnosis, Breast

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Architectural distortion detection in digital breast tomosynthesis with adaptive receptive field and adaptive convolution kernel shape

Yue Li, Zilong He, Xiangyuan Ma, Weimin Xu, Chanjuan Wen, Hui Zeng, Weixiong Zeng, Zeqi Wu, Genggeng Qin, Weiguo Chen, Yao Lu

Proceedings Volume 11597, 115972K (2021) https://doi.org/10.1117/12.2580836

KEYWORDS: Digital breast tomosynthesis, Advanced distributed simulations, Convolution, Architectural distortion, Tissues, Medical imaging, Data modeling, Breast

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Proceedings Article | 13 March 2019 Paper

Computer-aided detection and classification of microcalcification clusters on full field digital mammograms using deep convolution neural network

Guanxiong Cai, Yanhui Guo, Weiguo Chen, Hui Zeng, Yuanpin Zhou, Yao Lu

Proceedings Volume 10950, 109502J (2019) https://doi.org/10.1117/12.2512355

KEYWORDS: Mammography, Breast cancer, Convolution, Neural networks, Image processing, Computer-aided diagnosis, Classification systems, Breast, Computer aided diagnosis and therapy, Image enhancement

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