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Jaejun Yoo

Showing results (1-10 of 11) with videos related to

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IEEE Transactions on Medical Imaging|June 6, 2018
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual NetworkEunhee Kang, Won Chang, Jaejun Yoo, et al.
IEEE Transactions on Bio-Medical Engineering|July 12, 2018
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase NetworksDongwook Lee, Jaejun Yoo, Sungho Tak, et al.
Journal of Neuroscience Methods|April 10, 2016
Topological persistence vineyard for dynamic functional brain connectivity during resting and gaming stagesJaejun Yoo, Eun Young Kim, Yong Min Ahn, et al.
IEEE Transactions on Medical Imaging|May 27, 2021
Time-Dependent Deep Image Prior for Dynamic MRIJaejun Yoo, Kyong Hwan Jin, Harshit Gupta, et al.
Journal of Movement Disorders|January 31, 2018
Alteration in the Local and Global Functional Connectivity of Resting State Networks in Parkinson's DiseaseMaryam Ghahremani, Jaejun Yoo, Sun Ju Chung, et al.
Oral Radiology|October 29, 2024
Style harmonization of panoramic radiography using deep learningHak-Sun Kim, Jaejung Seol, Ji-Yun Lee, et al.
Magnetic Resonance in Medicine|February 6, 2018
Deep learning with domain adaptation for accelerated projection-reconstruction MRYoseob Han, Jaejun Yoo, Hak Hee Kim, et al.
European Radiology|April 19, 2025
Deep learning enhances reliability of dynamic contrast-enhanced MRI in diffuse gliomas: bypassing post-processing and providing uncertainty mapsYoung Wook Lyoo, Haneol Lee, Junhyeok Lee, et al.
Scientific Reports|February 18, 2025
Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatchPum Jun Kim, Dongyoung Kim, Joonwon Lee, et al.
Scientific Reports|June 2, 2026
Predicting diffusion-FLAIR mismatch from B1000 and ADC without FLAIR: A deep learning-based approachPum Jun Kim, Dongyoung Kim, Joonwon Lee, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
IEEE Transactions on Medical Imaging|June 6, 2018
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual NetworkEunhee Kang, Won Chang, Jaejun Yoo, et al.
IEEE Transactions on Bio-Medical Engineering|July 12, 2018
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase NetworksDongwook Lee, Jaejun Yoo, Sungho Tak, et al.
Journal of Neuroscience Methods|April 10, 2016
Topological persistence vineyard for dynamic functional brain connectivity during resting and gaming stagesJaejun Yoo, Eun Young Kim, Yong Min Ahn, et al.
IEEE Transactions on Medical Imaging|May 27, 2021
Time-Dependent Deep Image Prior for Dynamic MRIJaejun Yoo, Kyong Hwan Jin, Harshit Gupta, et al.
Journal of Movement Disorders|January 31, 2018
Alteration in the Local and Global Functional Connectivity of Resting State Networks in Parkinson's DiseaseMaryam Ghahremani, Jaejun Yoo, Sun Ju Chung, et al.
Oral Radiology|October 29, 2024
Style harmonization of panoramic radiography using deep learningHak-Sun Kim, Jaejung Seol, Ji-Yun Lee, et al.
Magnetic Resonance in Medicine|February 6, 2018
Deep learning with domain adaptation for accelerated projection-reconstruction MRYoseob Han, Jaejun Yoo, Hak Hee Kim, et al.
European Radiology|April 19, 2025
Deep learning enhances reliability of dynamic contrast-enhanced MRI in diffuse gliomas: bypassing post-processing and providing uncertainty mapsYoung Wook Lyoo, Haneol Lee, Junhyeok Lee, et al.
Scientific Reports|February 18, 2025
Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatchPum Jun Kim, Dongyoung Kim, Joonwon Lee, et al.
Scientific Reports|June 2, 2026
Predicting diffusion-FLAIR mismatch from B1000 and ADC without FLAIR: A deep learning-based approachPum Jun Kim, Dongyoung Kim, Joonwon Lee, et al.
Pageof 2