Dr. Jiaxing Tan Profile

Dr. Jiaxing Tan

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Publications (8)

Proceedings Article | 15 February 2021 Poster + Presentation + Paper

A comparison study of deep learning designs for improving low-dose CT denoising

Vincent Wang, Alice Wei, Jiaxing Tan, Siming Lu, Weiguo Cao, Yongfeng Gao

Proceedings Volume 11596, 115962N (2021) https://doi.org/10.1117/12.2582322

KEYWORDS: Denoising, Network architectures, Computed tomography

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Proceedings Article | 16 March 2020 Paper

Prior knowledge driven machine learning approach for PET sinogram data denoising

Siming Lu, Jiaxing Tan, Yongfeng Gao, Yongyi Shi, Zhengrong Liang

Proceedings Volume 11312, 113124A (2020) https://doi.org/10.1117/12.2549900

KEYWORDS: Positron emission tomography, Denoising, Machine learning, Convolution, Data modeling, Image quality, Medical imaging, Imaging systems, Signal to noise ratio, Sensors

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Proceedings Article | 16 March 2020 Paper

A deep learning based integration of multiple texture patterns from intensity, gradient and curvature GLCMs in differentiating the malignant from benign polyps

Shu Zhang, Weiguo Cao, Marc Pomeroy, Yongfeng Gao, Jiaxing Tan, Zhengrong Liang

Proceedings Volume 11314, 113143D (2020) https://doi.org/10.1117/12.2550014

KEYWORDS: Image classification, Medical imaging, Cancer, Computer aided diagnosis and therapy, Data integration, Convolutional neural networks, Image analysis

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Proceedings Article | 16 March 2020 Presentation + Paper

A multi-stage fusion strategy for multi-scale GLCM-CNN model in differentiating malignant from benign polyps

Jiaxing Tan, Shu Zhang, Weiguo Cao, Yongfeng Gao, Lihong Li, Yumei Huo, Zhengrong Liang

Proceedings Volume 11314, 113141S (2020) https://doi.org/10.1117/12.2549831

KEYWORDS: Tumor growth modeling, Feature extraction, Convolution, Visualization, Curium, Computer aided diagnosis and therapy, Visual process modeling, Colorectal cancer, Performance modeling, Tumors

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SPIE Journal Paper | 25 February 2020

Constructing a tissue-specific texture prior by machine learning from previous full-dose scan for Bayesian reconstruction of current ultralow-dose CT images

Yongfeng Gao, Jiaxing Tan, Yongyi Shi, Siming Lu, Amit Gupta, Haifang Li, Zhengrong Liang

JMI, Vol. 7, Issue 03, 032502, (February 2020) https://doi.org/10.1117/12.10.1117/1.JMI.7.3.032502

KEYWORDS: Tissues, Data modeling, Magnetorheological finishing, Machine learning, Image restoration, Reconstruction algorithms, Lung, Computed tomography, Performance modeling, Image quality

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Proceedings Article | 28 May 2019 Paper

A machine learning approach to construct a tissue-specific texture prior from previous full-dose CT for Bayesian reconstruction of current ultralow-dose CT images

Yongfeng Gao, Jiaxing Tan, Yongyi Shi, Siming Lu, Zhengrong Liang

Proceedings Volume 11072, 1107204 (2019) https://doi.org/10.1117/12.2534441

KEYWORDS: Tissues, Computed tomography, Data modeling, Machine learning, Performance modeling, Lung, Reconstruction algorithms

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Proceedings Article | 15 March 2019 Paper

Sharpness preserved sinogram synthesis using convolutional neural network for sparse-view CT imaging

Jiaxing Tan, Yongfeng Gao, Yumei Huo, Lihong Li, Zhengrong Liang

Proceedings Volume 10949, 109490E (2019) https://doi.org/10.1117/12.2512894

KEYWORDS: Computed tomography, Convolutional neural networks, Performance modeling, Feature extraction, X-ray computed tomography, Visual process modeling, Convolution, Tissues, Sensors, Image restoration

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Proceedings Article | 1 March 2019 Paper

Bayesian reconstruction of ultralow-dose CT images with texture prior from existing diagnostic full-dose CT database

Yongfeng Gao, Jiaxing Tan, Hao Zhang, William Moore, Priya Bhattacharji, Amit Gupta, Haifang Li, Hongbing Lu, Jianhua Ma, Zhengrong Liang

Proceedings Volume 10948, 1094855 (2019) https://doi.org/10.1117/12.2512787

KEYWORDS: Databases, Tissues, Computed tomography, Principal component analysis, Lung, Machine learning

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Showing 5 of 8 publications

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