Mr. Junchi Liu Profile

Junchi Liu

at Illinois Institute of Technology

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Publications (4)

Proceedings Article | 10 March 2020 Presentation + Paper

Artifact reduction in brain magnetic resonance imaging (MRI) by means of a dense residual network with K-space blending (DRN-KB)

Junchi Liu, Jie Deng

Proceedings Volume 11313, 113130N (2020) https://doi.org/10.1117/12.2549898

KEYWORDS: Magnetic resonance imaging, Image quality, Brain, Neuroimaging, Motion models, Denoising, Signal to noise ratio, Medical imaging, Convolutional neural networks, Medical research

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Proceedings Article | 6 July 2018 Paper

Radiation dose reduction in digital breast tomosynthesis (DBT) by means of neural network convolution (NNC) deep learning

Junchi Liu, Amin Zarshenas , Syed Ammar Qadir, Limin Yang, Laurie Fajardo, Kenji Suzuki

Proceedings Volume 10718, 1071814 (2018) https://doi.org/10.1117/12.2317789

KEYWORDS: Digital breast tomosynthesis, Breast, Image quality, Mammography, Neural networks, Breast cancer, Image quality standards, Denoising, Convolution, Cancer, Machine learning, Radiation

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Proceedings Article | 2 March 2018 Paper

Radiation dose reduction in digital breast tomosynthesis (DBT) by means of deep-learning-based supervised image processing

Junchi Liu, Amin Zarshenas, Ammar Qadir, Zheng Wei, Limin Yang, Laurie Fajardo, Kenji Suzuki

Proceedings Volume 10574, 105740F (2018) https://doi.org/10.1117/12.2293125

KEYWORDS: Digital breast tomosynthesis, Breast, Image quality, Mammography, Breast cancer, Image quality standards, Image processing, Neural networks, Denoising, Cancer

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Proceedings Article | 27 February 2018 Paper

Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): consolidation, ground-glass opacity (GGO), and normal opacity

Noriaki Hashimoto, Kenji Suzuki, Junchi Liu, Yasushi Hirano, Heber MacMahon, Shoji Kido

Proceedings Volume 10575, 1057536 (2018) https://doi.org/10.1117/12.2293550

KEYWORDS: Opacity, Lung, Neural networks, Convolution, Computed tomography, Classification systems, Image classification, Image segmentation, Computer aided diagnosis and therapy, Algorithm development

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