Mr. Byeongjoon Kim Profile

Byeongjoon Kim

at Yonsei Univ

SPIE Involvement:

Author

Publications (12)

Proceedings Article | 18 October 2022 Open Access

Sparsier2Sparse: weakly supervised learning for streak artifact reduction with unpaired sparse-view CT data

Seongjun Kim, Byeongjoon Kim, Jongduk Baek

Proceedings Volume 12304, 123040L (2022) https://doi.org/10.1117/12.2646428

KEYWORDS: X-ray computed tomography, Computed tomography, X-rays, Medical imaging, X-ray imaging, Convolutional neural networks

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Proceedings Article | 4 April 2022 Poster + Paper

A sequential approach using convolutional neural networks for motion artifacts reduction with a fast CT scan mode

Byeongjoon Kim, Yunsu Choi, Seunghyuk Moon, Jongduk Baek

Proceedings Volume 12031, 120312T (2022) https://doi.org/10.1117/12.2608473

KEYWORDS: Computed tomography, Convolutional neural networks, Image quality, X-ray computed tomography, Reconstruction algorithms, Data acquisition

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Proceedings Article | 4 April 2022 Poster + Paper

Streak artifacts reduction algorithm using an implicit neural representation in sparse-view CT

Byeongjoon Kim, Hyunjung Shim, Jongduk Baek

Proceedings Volume 12031, 120312N (2022) https://doi.org/10.1117/12.2610722

KEYWORDS: Computed tomography, Reconstruction algorithms, CT reconstruction, Neural networks, Image restoration

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

A hybrid domain approach to reduce streak artifacts of sparse view CT image via convolutional neural network

Seongjun Kim, Byeongjoon Kim, Jongduk Baek

Proceedings Volume 11595, 115952L (2021) https://doi.org/10.1117/12.2580113

KEYWORDS: Computed tomography, Convolutional neural networks, Image filtering, Reconstruction algorithms, Data conversion, Data acquisition

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

CNN-based CT denoising with an accurate image domain noise insertion technique

Byeongjoon Kim, Sarah Divel, Norbert Pelc, Jongduk Baek

Proceedings Volume 11595, 1159545 (2021) https://doi.org/10.1117/12.2580997

KEYWORDS: Denoising, Computed tomography, Modulation transfer functions, Image quality, Statistical analysis, Optical filters, Image filtering, Gaussian filters, Error analysis, Convolutional neural networks

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Proceedings Article | 16 March 2020 Paper

A performance comparison of convolutional neural network based anthropomorphic model observer and linear model observer for signal-known statistically detection tasks

Minah Han, Byeongjoon Kim, Jongduk Baek

Proceedings Volume 11316, 1131612 (2020) https://doi.org/10.1117/12.2549487

KEYWORDS: Signal detection, Convolutional neural networks, Breast, Computed tomography

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Proceedings Article | 16 March 2020 Paper

Convolutional neural network-based anthropomorphic model observer for breast cone-beam CT images

Byeongjoon Kim, Minah Han, Jongduk Baek

Proceedings Volume 11316, 113160Y (2020) https://doi.org/10.1117/12.2549168

KEYWORDS: Breast, Performance modeling, Eye models, Data modeling, Computed tomography, Neural networks, Convolutional neural networks, Reconstruction algorithms, Convolution

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Proceedings Article | 1 March 2019 Paper

Multidimensional noise reduction in C-arm cone-beam CT via 2D-based Landweber iteration and 3D-based deep neural networks

Dahim Choi, Juhee Kim, Seung-Hoon Chae, Byeongjoon Kim, Jongduk Baek, Andreas Maier, Rebecca Fahrig, Hyun-Seok Park, Jang-Hwan Choi

Proceedings Volume 10948, 1094837 (2019) https://doi.org/10.1117/12.2512723

KEYWORDS: Denoising, Computed tomography, 3D modeling, Image processing, Image filtering, 3D image processing, Image quality, Reconstruction algorithms, Neural networks, Nonlinear filtering

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Proceedings Article | 1 March 2019 Paper

Investigation on slice direction dependent denoising performance of convolutional neural network in cone-beam CT images

Eunhyeok Lee, Byeongjoon Kim, Jongduk Baek

Proceedings Volume 10948, 1094848 (2019) https://doi.org/10.1117/12.2512186

KEYWORDS: Denoising, Convolutional neural networks, Computed tomography, Reconstruction algorithms, Data acquisition, X-ray computed tomography, Network architectures, Data modeling

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