1620 related articles for article (PubMed ID: 31006909)
1. Conditional generative adversarial network for 3D rigid-body motion correction in MRI.
Johnson PM; Drangova M
Magn Reson Med; 2019 Sep; 82(3):901-910. PubMed ID: 31006909
[TBL] [Abstract][Full Text] [Related]
2. Retrospective respiratory motion correction in cardiac cine MRI reconstruction using adversarial autoencoder and unsupervised learning.
Ghodrati V; Bydder M; Ali F; Gao C; Prosper A; Nguyen KL; Hu P
NMR Biomed; 2021 Feb; 34(2):e4433. PubMed ID: 33258197
[TBL] [Abstract][Full Text] [Related]
3. MRI motion artifact reduction using a conditional diffusion probabilistic model (MAR-CDPM).
Safari M; Yang X; Fatemi A; Archambault L
Med Phys; 2024 Apr; 51(4):2598-2610. PubMed ID: 38009583
[TBL] [Abstract][Full Text] [Related]
4. Retrospective correction of motion-affected MR images using deep learning frameworks.
Küstner T; Armanious K; Yang J; Yang B; Schick F; Gatidis S
Magn Reson Med; 2019 Oct; 82(4):1527-1540. PubMed ID: 31081955
[TBL] [Abstract][Full Text] [Related]
5. Brain tumor classification for MRI images using dual-discriminator conditional generative adversarial network.
Selvi T K; Sumaiya Begum A; Poonkuzhali P; Aarthi R
Electromagn Biol Med; 2024 Apr; 43(1-2):81-94. PubMed ID: 38461438
[TBL] [Abstract][Full Text] [Related]
6. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose.
Wang Y; Yu B; Wang L; Zu C; Lalush DS; Lin W; Wu X; Zhou J; Shen D; Zhou L
Neuroimage; 2018 Jul; 174():550-562. PubMed ID: 29571715
[TBL] [Abstract][Full Text] [Related]
7. Generating synthesized computed tomography from CBCT using a conditional generative adversarial network for head and neck cancer patients.
Zhang Y; Ding SG; Gong XC; Yuan XX; Lin JF; Chen Q; Li JG
Technol Cancer Res Treat; 2022; 21():15330338221085358. PubMed ID: 35262422
[No Abstract] [Full Text] [Related]
8. Conditional Generative Adversarial Networks Aided Motion Correction of Dynamic
Shiyam Sundar LK; Iommi D; Muzik O; Chalampalakis Z; Klebermass EM; Hienert M; Rischka L; Lanzenberger R; Hahn A; Pataraia E; Traub-Weidinger T; Hummel J; Beyer T
J Nucl Med; 2021 Jun; 62(6):871-879. PubMed ID: 33246982
[TBL] [Abstract][Full Text] [Related]
9. Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation.
Hagiwara A; Otsuka Y; Hori M; Tachibana Y; Yokoyama K; Fujita S; Andica C; Kamagata K; Irie R; Koshino S; Maekawa T; Chougar L; Wada A; Takemura MY; Hattori N; Aoki S
AJNR Am J Neuroradiol; 2019 Feb; 40(2):224-230. PubMed ID: 30630834
[TBL] [Abstract][Full Text] [Related]
10. Network Accelerated Motion Estimation and Reduction (NAMER): Convolutional neural network guided retrospective motion correction using a separable motion model.
Haskell MW; Cauley SF; Bilgic B; Hossbach J; Splitthoff DN; Pfeuffer J; Setsompop K; Wald LL
Magn Reson Med; 2019 Oct; 82(4):1452-1461. PubMed ID: 31045278
[TBL] [Abstract][Full Text] [Related]
11. High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN).
Li Z; Tian Q; Ngamsombat C; Cartmell S; Conklin J; Filho ALMG; Lo WC; Wang G; Ying K; Setsompop K; Fan Q; Bilgic B; Cauley S; Huang SY
Med Phys; 2022 Feb; 49(2):1000-1014. PubMed ID: 34961944
[TBL] [Abstract][Full Text] [Related]
12. Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients.
Tie X; Lam SK; Zhang Y; Lee KH; Au KH; Cai J
Med Phys; 2020 Apr; 47(4):1750-1762. PubMed ID: 32012292
[TBL] [Abstract][Full Text] [Related]
13. Multimodal MRI synthesis using unified generative adversarial networks.
Dai X; Lei Y; Fu Y; Curran WJ; Liu T; Mao H; Yang X
Med Phys; 2020 Dec; 47(12):6343-6354. PubMed ID: 33053202
[TBL] [Abstract][Full Text] [Related]
14. Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks.
Dar SU; Yurt M; Karacan L; Erdem A; Erdem E; Cukur T
IEEE Trans Med Imaging; 2019 Oct; 38(10):2375-2388. PubMed ID: 30835216
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of motion artefact reduction depending on the artefacts' directions in head MRI using conditional generative adversarial networks.
Usui K; Muro I; Shibukawa S; Goto M; Ogawa K; Sakano Y; Kyogoku S; Daida H
Sci Rep; 2023 May; 13(1):8526. PubMed ID: 37237139
[TBL] [Abstract][Full Text] [Related]
16. Deep learning-based motion quantification from k-space for fast model-based magnetic resonance imaging motion correction.
Hossbach J; Splitthoff DN; Cauley S; Clifford B; Polak D; Lo WC; Meyer H; Maier A
Med Phys; 2023 Apr; 50(4):2148-2161. PubMed ID: 36433748
[TBL] [Abstract][Full Text] [Related]
17. Deep learning for improving ZTE MRI images in free breathing.
Papp D; Castillo T JM; Wielopolski PA; Ciet P; Veenland JF; Kotek G; Hernandez-Tamames J
Magn Reson Imaging; 2023 May; 98():97-104. PubMed ID: 36681310
[TBL] [Abstract][Full Text] [Related]
18. Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks.
Gaj S; Yang M; Nakamura K; Li X
Magn Reson Med; 2020 Jul; 84(1):437-449. PubMed ID: 31793071
[TBL] [Abstract][Full Text] [Related]
19. Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.
Lee J; Seo H; Lee W; Park H
Magn Reson Med; 2024 Jul; 92(1):28-42. PubMed ID: 38282279
[TBL] [Abstract][Full Text] [Related]
20. Motion artifact removal in coronary CT angiography based on generative adversarial networks.
Zhang L; Jiang B; Chen Q; Wang L; Zhao K; Zhang Y; Vliegenthart R; Xie X
Eur Radiol; 2023 Jan; 33(1):43-53. PubMed ID: 35829786
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
