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Showing results 1 to 9 of 9

1
Cycle-consistent adversarial denoising network for multiphase coronary CT angiography

Kang, Eunhee; Koo, Hyun Jung; Yang, Dong Hyun; Seo, Joon Bum; Ye, Jong Chul, MEDICAL PHYSICS, v.46, no.2, pp.550 - 562, 2019-02

2
Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study

Kim, Youngjune; Oh, Dong Yul; Chang, Won; Kang, Eunhee; Ye, Jong Chul; Lee, Kyeorye; Kim, Hae Young; et al, EUROPEAN RADIOLOGY, v.31, no.11, pp.8755 - 8764, 2021-11

3
Doubly supervised embedding based on class labels and intrinsic clusters for high-dimensional data visualization

Kim, Hannah; Choo, Jaegul; Reddy, Chandan K.; Park, Haesun, NEUROCOMPUTING, v.150, pp.570 - 582, 2015-02

4
k-Space deep learning for reference-free EPI ghost correction

Lee, Juyoung; Han, Yoseob; Ryu, Jae-Kyun; Park, Jang-Yeon; Ye, Jong Chul, MAGNETIC RESONANCE IN MEDICINE, v.82, no.6, pp.2299 - 2313, 2019-12

5
Projection reconstruction MR imaging using FOCUSS

Ye, Jong-Chul; Tak, Sung-Ho; Han, Ye Ji; Park, Hyun-Wook, MAGNETIC RESONANCE IN MEDICINE, v.57, no.4, pp.764 - 775, 2007-04

6
Sparsity driven metal part reconstruction for artifact removal in dental CT

Choi, Ji-Young; Kim, Kyung-Sang; Kim, Min-Woo; Seong, Won; Ye, Jong-Chul, JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY, v.19, no.4, pp.457 - 475, 2011-10

7
Unpaired MR Motion Artifact Deep Learning Using Outlier-Rejecting Bootstrap Aggregation

Oh, Gyutaek; Lee, Jeong Eun; Ye, Jong Chul, IEEE TRANSACTIONS ON MEDICAL IMAGING, v.40, no.11, pp.3125 - 3139, 2021-11

8
Unsupervised CT Metal Artifact Learning Using Attention-Guided beta-CycleGAN

Lee, Junghyun; Gu, Jawook; Ye, Jong Chul, IEEE TRANSACTIONS ON MEDICAL IMAGING, v.40, no.12, pp.3932 - 3944, 2021-12

9
Weakly-supervised progressive denoising with unpaired CT images

Kim, Byeongjoon; Shim, Hyunjung; Baek, Jongduk, MEDICAL IMAGE ANALYSIS, v.71, 2021-07

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