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2020 – today
- 2023
[j4]Heewon Yoon
, Yongwon Cho, Kyung-Sik Ahn, Hee-Gone Lee, Chang Ho Kang, Beom Jin Park:
Using a convolutional neural network model to derive imaging landmarks for lumbar spine numbering on axial magnetic resonance images. Int. J. Imaging Syst. Technol. 33(2): 547-555 (2023)- [c1]Seungeun Lee, Sung Ho Hwang, Saelin Oh, Beom Jin Park, Yongwon Cho:
Multi-input Vision Transformer with Similarity Matching. PRIME@MICCAI 2023: 184-193 - 2022
- [j3]Yongwon Cho, Yeo Eun Han, Min Ju Kim, Beom Jin Park, Ki Choon Sim, Deuk Jae Sung, Na Yeon Han, Yang Shin Park:
Computer-aided hepatocellular carcinoma detection on the hepatobiliary phase of gadoxetic acid-enhanced magnetic resonance imaging using a convolutional neural network: Feasibility evaluation with multi-sequence data. Comput. Methods Programs Biomed. 225: 107032 (2022) - 2021
- [j2]Yongwon Cho, Sung Ho Hwang, Yu-Whan Oh, Byung-Joo Ham, Min Ju Kim, Beom Jin Park:
Deep convolution neural networks to differentiate between COVID-19 and other pulmonary abnormalities on chest radiographs: Evaluation using internal and external datasets. Int. J. Imaging Syst. Technol. 31(3): 1087-1104 (2021) - [j1]Yongwon Cho, Min Ju Kim, Beom Jin Park, Ki Choon Sim, Yeom Suk Keu, Yeo Eun Han, Deuk Jae Sung, Na Yeon Han:
Active Learning for Efficient Segmentation of Liver with Convolutional Neural Network-Corrected Labeling in Magnetic Resonance Imaging-Derived Proton Density Fat Fraction. J. Digit. Imaging 34(5): 1225-1236 (2021)
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