These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
1401 related articles for article (PubMed ID: 34796526)
1. Spatial adaptive and transformer fusion network (STFNet) for low-count PET blind denoising with MRI. Zhang L; Xiao Z; Zhou C; Yuan J; He Q; Yang Y; Liu X; Liang D; Zheng H; Fan W; Zhang X; Hu Z Med Phys; 2022 Jan; 49(1):343-356. PubMed ID: 34796526 [TBL] [Abstract][Full Text] [Related]
2. STEDNet: Swin transformer-based encoder-decoder network for noise reduction in low-dose CT. Zhu L; Han Y; Xi X; Fu H; Tan S; Liu M; Yang S; Liu C; Li L; Yan B Med Phys; 2023 Jul; 50(7):4443-4458. PubMed ID: 36708286 [TBL] [Abstract][Full Text] [Related]
4. Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss. Ouyang J; Chen KT; Gong E; Pauly J; Zaharchuk G Med Phys; 2019 Aug; 46(8):3555-3564. PubMed ID: 31131901 [TBL] [Abstract][Full Text] [Related]
5. Utilizing deep learning techniques to improve image quality and noise reduction in preclinical low-dose PET images in the sinogram domain. Manoj Doss KK; Chen JC Med Phys; 2024 Jan; 51(1):209-223. PubMed ID: 37966121 [TBL] [Abstract][Full Text] [Related]
6. Full-count PET recovery from low-count image using a dilated convolutional neural network. Spuhler K; Serrano-Sosa M; Cattell R; DeLorenzo C; Huang C Med Phys; 2020 Oct; 47(10):4928-4938. PubMed ID: 32687608 [TBL] [Abstract][Full Text] [Related]
7. 3D multi-modality Transformer-GAN for high-quality PET reconstruction. Wang Y; Luo Y; Zu C; Zhan B; Jiao Z; Wu X; Zhou J; Shen D; Zhou L Med Image Anal; 2024 Jan; 91():102983. PubMed ID: 37926035 [TBL] [Abstract][Full Text] [Related]
8. Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapy. Olberg S; Zhang H; Kennedy WR; Chun J; Rodriguez V; Zoberi I; Thomas MA; Kim JS; Mutic S; Green OL; Park JC Med Phys; 2019 Sep; 46(9):4135-4147. PubMed ID: 31309586 [TBL] [Abstract][Full Text] [Related]
9. Deep learning generation of preclinical positron emission tomography (PET) images from low-count PET with task-based performance assessment. Dutta K; Laforest R; Luo J; Jha AK; Shoghi KI Med Phys; 2024 Jun; 51(6):4324-4339. PubMed ID: 38710222 [TBL] [Abstract][Full Text] [Related]
10. Generation of synthetic PET/MR fusion images from MR images using a combination of generative adversarial networks and conditional denoising diffusion probabilistic models based on simultaneous 18F-FDG PET/MR image data of pyogenic spondylodiscitis. Jung E; Kong E; Yu D; Yang H; Chicontwe P; Park SH; Jeon I Spine J; 2024 Aug; 24(8):1467-1477. PubMed ID: 38615932 [TBL] [Abstract][Full Text] [Related]
11. Image reconstruction using UNET-transformer network for fast and low-dose PET scans. Kaviani S; Sanaat A; Mokri M; Cohalan C; Carrier JF Comput Med Imaging Graph; 2023 Dec; 110():102315. PubMed ID: 38006648 [TBL] [Abstract][Full Text] [Related]
12. High-quality PET image synthesis from ultra-low-dose PET/MRI using bi-task deep learning. Sun H; Jiang Y; Yuan J; Wang H; Liang D; Fan W; Hu Z; Zhang N Quant Imaging Med Surg; 2022 Dec; 12(12):5326-5342. PubMed ID: 36465830 [TBL] [Abstract][Full Text] [Related]
13. A novel denoising method for low-dose CT images based on transformer and CNN. Zhang J; Shangguan Z; Gong W; Cheng Y Comput Biol Med; 2023 Sep; 163():107162. PubMed ID: 37327755 [TBL] [Abstract][Full Text] [Related]
14. Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network. Chen H; Chen X; Lin L; Cai S; Cai C; Chen Z; Xu J; Chen L Magn Reson Med; 2023 Nov; 90(5):2071-2088. PubMed ID: 37332198 [TBL] [Abstract][Full Text] [Related]
15. Denoising of 3D magnetic resonance images using a residual encoder-decoder Wasserstein generative adversarial network. Ran M; Hu J; Chen Y; Chen H; Sun H; Zhou J; Zhang Y Med Image Anal; 2019 Jul; 55():165-180. PubMed ID: 31085444 [TBL] [Abstract][Full Text] [Related]
16. Low-dose CT denoising with a high-level feature refinement and dynamic convolution network. Yang S; Pu Q; Lei C; Zhang Q; Jeon S; Yang X Med Phys; 2023 Jun; 50(6):3597-3611. PubMed ID: 36542402 [TBL] [Abstract][Full Text] [Related]
17. Self-supervised structural similarity-based convolutional neural network for cardiac diffusion tensor image denoising. Yuan N; Wang L; Ye C; Deng Z; Zhang J; Zhu Y Med Phys; 2023 Oct; 50(10):6137-6150. PubMed ID: 36775901 [TBL] [Abstract][Full Text] [Related]
18. An investigation of quantitative accuracy for deep learning based denoising in oncological PET. Lu W; Onofrey JA; Lu Y; Shi L; Ma T; Liu Y; Liu C Phys Med Biol; 2019 Aug; 64(16):165019. PubMed ID: 31307019 [TBL] [Abstract][Full Text] [Related]
19. Structure-preserving low-dose computed tomography image denoising using a deep residual adaptive global context attention network. Zhang Y; Hao D; Lin Y; Sun W; Zhang J; Meng J; Ma F; Guo Y; Lu H; Li G; Liu J Quant Imaging Med Surg; 2023 Oct; 13(10):6528-6545. PubMed ID: 37869272 [TBL] [Abstract][Full Text] [Related]
20. Full-dose whole-body PET synthesis from low-dose PET using high-efficiency denoising diffusion probabilistic model: PET consistency model. Pan S; Abouei E; Peng J; Qian J; Wynne JF; Wang T; Chang CW; Roper J; Nye JA; Mao H; Yang X Med Phys; 2024 Aug; 51(8):5468-5478. PubMed ID: 38588512 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]