Prof. Dan Ruan Profile

Prof. Dan Ruan

at Univ of California Los Angeles

SPIE Involvement:

Author

Publications (8)

Proceedings Article | 3 April 2024 Poster + Paper

Self-supervised learning without annotations to improve lung chest x-ray segmentation

Jin Kim, Matthew Brown, Dan Ruan

Proceedings Volume 12927, 1292737 (2024) https://doi.org/10.1117/12.3008582

KEYWORDS: Image segmentation, Chest imaging, Lung, Medical imaging, Binary data, Image processing, Deep learning, Deep convolutional neural networks

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SPIE Journal Paper | 28 December 2020

Imposing implicit feasibility constraints on deformable image registration using a statistical generative model

Yudi Sang, Xianglei Xing, YingNian Wu, Dan Ruan

JMI, Vol. 7, Issue 06, 064005, (December 2020) https://doi.org/10.1117/12.10.1117/1.JMI.7.6.064005

KEYWORDS: Image registration, 3D modeling, Statistical modeling, Image segmentation, Cardiovascular magnetic resonance imaging, 3D image processing, Lung, Computed tomography, Tissues, Digital imaging

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Proceedings Article | 16 March 2020 Paper

Iterative reconstruction of cone-beam breast CT using plug-and-play projected gradient descent

Qihui Lyu, Tianye Niu, Dan Ruan, Ke Sheng

Proceedings Volume 11312, 113124J (2020) https://doi.org/10.1117/12.2549787

KEYWORDS: Breast, Reconstruction algorithms, Model-based design, Image restoration, Signal to noise ratio, Denoising, Image quality standards, Computed tomography, Data acquisition, Convolutional neural networks

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Proceedings Article | 10 March 2020 Paper

Imposing implicit feasibility constraints on deformable image registration using a statistical generative model

Yudi Sang, Xianglei Xing, Yingnian Wu, Dan Ruan

Proceedings Volume 11313, 113132V (2020) https://doi.org/10.1117/12.2549193

KEYWORDS: Image registration, Statistical modeling, Tissues, Motion models, Magnetic resonance imaging, Deconvolution, Digital imaging, Cardiovascular magnetic resonance imaging, Optimization (mathematics)

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Proceedings Article | 2 March 2020 Paper

Feasibility of predicting pancreatic neuroendocrine tumor grade using deep features from unsupervised learning

Yidong Wan, Lei Xu, Pengfei Yang, Zuozhen Cao, Chen Luo, Xiaoyong Shen, Yan Wu, Dan Ruan, Tianye Niu

Proceedings Volume 11318, 113180O (2020) https://doi.org/10.1117/12.2548723

KEYWORDS: Machine learning, Tumors, Neural networks, Feature extraction, Medicine, Medical imaging, Algorithm development, Performance modeling, Process modeling, Feature selection

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Proceedings Article | 15 March 2019 Presentation + Paper

Iterative reconstruction for low dose CT using Plug-and-Play alternating direction method of multipliers (ADMM) framework

Qihui Lyu, Dan Ruan, John Hoffman, Ryan Neph, Michael McNitt-Gray, Ke Sheng

Proceedings Volume 10949, 1094906 (2019) https://doi.org/10.1117/12.2512484

KEYWORDS: Image processing, Reconstruction algorithms, Computed tomography, Image resolution, Denoising, Model-based design, Image restoration, Image filtering, Data acquisition

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Proceedings Article | 2 March 2018 Paper

Coupling reconstruction and motion estimation for dynamic MRI through optical flow constraint

Ningning Zhao, Daniel O'Connor, Wenbo Gu, Dan Ruan, Adrian Basarab, Ke Sheng

Proceedings Volume 10574, 1057429 (2018) https://doi.org/10.1117/12.2293878

KEYWORDS: Motion estimation, Magnetic resonance imaging, Reconstruction algorithms, Optical flow, Seaborgium, Personal digital assistants, Roentgenium, Compressed sensing, Optimization (mathematics), Data acquisition

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Proceedings Article | 10 March 2006 Paper

Nonrigid registration using regularization that accommodates local tissue rigidity

Dan Ruan, Jeffrey Fessler, Michael Roberson, James Balter, Marc Kessler

Proceedings Volume 6144, 614412 (2006) https://doi.org/10.1117/12.653870

KEYWORDS: Tissues, Image registration, Bone, Image segmentation, X-ray computed tomography, Medical imaging, Image filtering, X-rays, Computed tomography, Lung

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Showing 5 of 8 publications

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