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.
169 related articles for article (PubMed ID: 36772535)
1. RDASNet: Image Denoising via a Residual Dense Attention Similarity Network. Tao H; Guo W; Han R; Yang Q; Zhao J Sensors (Basel); 2023 Jan; 23(3):. PubMed ID: 36772535 [TBL] [Abstract][Full Text] [Related]
2. Attention-guided CNN for image denoising. Tian C; Xu Y; Li Z; Zuo W; Fei L; Liu H Neural Netw; 2020 Apr; 124():117-129. PubMed ID: 31991307 [TBL] [Abstract][Full Text] [Related]
3. Global and local feature extraction based on convolutional neural network residual learning for MR image denoising. Li M; Yun J; Liu D; Jiang D; Xiong H; Jiang D; Hu S; Liu R; Li G Phys Med Biol; 2024 Oct; 69(20):. PubMed ID: 39312945 [No Abstract] [Full Text] [Related]
4. Incorporation of residual attention modules into two neural networks for low-dose CT denoising. Li M; Du Q; Duan L; Yang X; Zheng J; Jiang H; Li M Med Phys; 2021 Jun; 48(6):2973-2990. PubMed ID: 33890681 [TBL] [Abstract][Full Text] [Related]
5. Denoising of 3D Brain MR Images with Parallel Residual Learning of Convolutional Neural Network Using Global and Local Feature Extraction. Wu L; Hu S; Liu C Comput Intell Neurosci; 2021; 2021():5577956. PubMed ID: 34054939 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. RatUNet: residual U-Net based on attention mechanism for image denoising. Zhang H; Lian Q; Zhao J; Wang Y; Yang Y; Feng S PeerJ Comput Sci; 2022; 8():e970. PubMed ID: 35634105 [TBL] [Abstract][Full Text] [Related]
8. Considering Image Information and Self-Similarity: A Compositional Denoising Network. Zhang J; Zhu Y; Yu W; Ma J Sensors (Basel); 2023 Jun; 23(13):. PubMed ID: 37447765 [TBL] [Abstract][Full Text] [Related]
9. Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography. Usui K; Ogawa K; Goto M; Sakano Y; Kyougoku S; Daida H Vis Comput Ind Biomed Art; 2021 Jul; 4(1):21. PubMed ID: 34304321 [TBL] [Abstract][Full Text] [Related]
10. An application of deep dual convolutional neural network for enhanced medical image denoising. Sahu A; Rana KPS; Kumar V Med Biol Eng Comput; 2023 May; 61(5):991-1004. PubMed ID: 36639550 [TBL] [Abstract][Full Text] [Related]
12. Denoising of three-dimensional fast spin echo magnetic resonance images of knee joints using spatial-variant noise-relevant residual learning of convolution neural network. Zhao S; Cahill DG; Li S; Xiao F; Blu T; Griffith JF; Chen W Comput Biol Med; 2022 Dec; 151(Pt A):106295. PubMed ID: 36423533 [TBL] [Abstract][Full Text] [Related]
13. A new visual State Space Model for low-dose CT denoising. Huang J; Zhong A; Wei Y Med Phys; 2024 Dec; 51(12):8851-8864. PubMed ID: 39231014 [TBL] [Abstract][Full Text] [Related]
14. Image denoising using deep CNN with batch renormalization. Tian C; Xu Y; Zuo W Neural Netw; 2020 Jan; 121():461-473. PubMed ID: 31629201 [TBL] [Abstract][Full Text] [Related]
15. Multi-Branch Network for Color Image Denoising Using Dilated Convolution and Attention Mechanisms. Duong MT; Nguyen Thi BT; Lee S; Hong MC Sensors (Basel); 2024 Jun; 24(11):. PubMed ID: 38894398 [TBL] [Abstract][Full Text] [Related]
17. A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention. Zhang J; Ye L; Gong W; Chen M; Liu G; Cheng Y J Imaging Inform Med; 2024 Sep; ():. PubMed ID: 39261373 [TBL] [Abstract][Full Text] [Related]
18. An efficient lightweight network for image denoising using progressive residual and convolutional attention feature fusion. Tiantian W; Hu Z; Guan Y Sci Rep; 2024 Apr; 14(1):9554. PubMed ID: 38664440 [TBL] [Abstract][Full Text] [Related]
19. A novel denoising method for CT images based on U-net and multi-attention. Zhang J; Niu Y; Shangguan Z; Gong W; Cheng Y Comput Biol Med; 2023 Jan; 152():106387. PubMed ID: 36495750 [TBL] [Abstract][Full Text] [Related]
20. SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network. Li M; Hsu W; Xie X; Cong J; Gao W IEEE Trans Med Imaging; 2020 Jul; 39(7):2289-2301. PubMed ID: 31985412 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]