- High Resolution Time Resolved Contrast Enhanced MR Angiography Using k-t FOCUSS
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Jung H, Kim EY, Ye JC
- KMID: 1782989
- J Korean Soc Magn Reson Med.
- 2010 Jun;14(1):10-20.
- doi: 10.13104/jksmrm.2010.14.1.10
PURPOSE: Recently, the Recon Challenge at the 2009 ISMRM workshop on Data Sampling and Image Reconstruction at Sedona, Arizona was held to evaluate feasibility of highly accelerated acquisition of time... -
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- Alteration in the Local and Global Functional Connectivity of Resting State Networks in Parkinson's Disease
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Ghahremani M, Yoo J, Chung SJ, Yoo K, Ye JC, Jeong Y
- KMID: 2405198
- J Mov Disord.
- 2018 Jan;11(1):13-23.
- doi: 10.14802/jmd.17061
OBJECTIVE: Parkinson’s disease (PD) is a neurodegenerative disorder that mainly leads to the impairment of patients’ motor function, as well as of cognition, as it progresses. This study tried to... -
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- Tetrandrine Exerts a Radiosensitization Effect on Human Glioma through Inhibiting Proliferation by Attenuating ERK Phosphorylation
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Ma JW, Zhang Y, Ye JC, Li R, Wen YL, Huang JX, Zhong XY
- KMID: 2375039
- Biomol Ther.
- 2017 Mar;25(2):186-193.
- doi: 10.4062/biomolther.2016.044
Tetrandrine (Tet), a bisbenzylisoquinoline alkaloid, has been reported to have a radiosensitization effect on tumors. However, its effects on human glioma and the specific molecular mechanisms of these effects remain... -
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- Unsupervised Deformable Image Registration Using Polyphase UNet for 3D Brain MRI Volumes
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Martin AD, Kim B, Ye JC
- KMID: 2510452
- Investig Magn Reson Imaging.
- 2020 Dec;24(4):223-231.
- doi: 10.13104/imri.2020.24.4.223
Purpose: Image registration is a fundamental task in various medical imaging studies and clinical image analyses, such as comparison of patient data with anatomical structures. In order to solve the... -
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- Dehazing Algorithm for Enhancing Fundus Photographs Using Dark Channel and Bright Channel Prior
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Park S, Chung H, Ye JC, Yi K
- KMID: 2550475
- J Korean Ophthalmol Soc.
- 2024 Jan;65(1):44-52.
- doi: 10.3341/jkos.2024.65.1.44
Purpose: We present a dehazing algorithm using dark channel prior (DCP) and bright channel prior (BCP) to enhance the quality of retinal images obtained through conventional fundus photography. Methods: A retrospective... -
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- Erratum: Correction of Author Name and Affiliation in the Article “Artificial Intelligence in Health Care: Current Applications and Issues”
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Park CW, Seo SW, Kang N, Ko B, Choi BW, Park CM, Chang DK, Kim H, Kim H, Lee H, Jang J, Ye JC, Jeon JH, Seo JB, Kim KJ, Jung KH, Kim N, Paek S, Shin SY, Yoo S, Choi YS, Kim Y, Yoon HJ
- KMID: 2509530
- J Korean Med Sci.
- 2020 Dec;35(48):e425.
- doi: 10.3346/jkms.2020.35.e425
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- Deep Learning-Enabled Detection of Pneumoperitoneum in Supine and Erect Abdominal Radiography: Modeling Using Transfer Learning and Semi-Supervised Learning
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Park S, Ye JC, Lee ES, Cho G, Yoon JW, Choi JH, Joo I, Lee YJ
- KMID: 2542862
- Korean J Radiol.
- 2023 Jun;24(6):541-552.
- doi: 10.3348/kjr.2022.1032
Objective: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection... -
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- Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm
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Shin YJ, Chang W, Ye JC, Kang E, Oh DY, Lee YJ, Park JH, Kim YH
- KMID: 2470759
- Korean J Radiol.
- 2020 Mar;21(3):356-364.
- doi: 10.3348/kjr.2019.0413
OBJECTIVE: To compare the image quality of low-dose (LD) computed tomography (CT) obtained using a deep learning-based denoising algorithm (DLA) with LD CT images reconstructed with a filtered back projection... -
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- Radiation Dose Reduction in Digital Mammography by Deep-Learning Algorithm Image Reconstruction: A Preliminary Study
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Ha SM, Kim HH, Kang E, Seo BK, Choi N, Kim TH, Ku YJ, Ye JC
- KMID: 2527797
- J Korean Soc Radiol.
- 2022 Mar;83(2):344-359.
- doi: 10.3348/jksr.2020.0152
Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were... -
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- Artificial Intelligence in Health Care: Current Applications and Issues
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Park CW, Seo SW, Kang N, Ko BS, Choi BW, Park CM, Chang DK, Kim H, Kim Hc, Lee Hn, Jang Jh, Ye JC, Jeon JH, Seo JB, Kim KJ, Jung KH, Kim N, Paek Sw, Shin SY, Yoo Sy, Choi YS, Kim Y, Yoon HJ
- KMID: 2508431
- J Korean Med Sci.
- 2020 Nov;35(42):e379.
- doi: 10.3346/jkms.2020.35.e379
In recent years, artificial intelligence (AI) technologies have greatly advanced and become a reality in many areas of our daily lives. In the health care field, numerous efforts are being... -
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- Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease
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Hwang HJ, Kim H, Seo JB, Ye JC, Oh G, Lee SM, Jang R, Yun J, Kim N, Park HJ, Lee HY, Yoon SH, Shin KE, Lee JW, Kwon W, Sun JS, You S, Chung MH, Gil BM, Lim JK, Lee Y, Hong SJ, Choi YW
- KMID: 2544923
- Korean J Radiol.
- 2023 Aug;24(8):807-820.
- doi: 10.3348/kjr.2023.0088
Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial... -
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