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.
156 related articles for article (PubMed ID: 36279348)
1. Transformer With Double Enhancement for Low-Dose CT Denoising. Li H; Yang X; Yang S; Wang D; Jeon G IEEE J Biomed Health Inform; 2023 Oct; 27(10):4660-4671. PubMed ID: 36279348 [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. Unpaired low-dose computed tomography image denoising using a progressive cyclical convolutional neural network. Li Q; Li R; Li S; Wang T; Cheng Y; Zhang S; Wu W; Zhao J; Qiang Y; Wang L Med Phys; 2024 Feb; 51(2):1289-1312. PubMed ID: 36841936 [TBL] [Abstract][Full Text] [Related]
5. Learning low-dose CT degradation from unpaired data with flow-based model. Liu X; Liang X; Deng L; Tan S; Xie Y Med Phys; 2022 Dec; 49(12):7516-7530. PubMed ID: 35880375 [TBL] [Abstract][Full Text] [Related]
7. 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]
8. Two stage residual CNN for texture denoising and structure enhancement on low dose CT image. Huang L; Jiang H; Li S; Bai Z; Zhang J Comput Methods Programs Biomed; 2020 Feb; 184():105115. PubMed ID: 31627148 [TBL] [Abstract][Full Text] [Related]
9. Adapting low-dose CT denoisers for texture preservation using zero-shot local noise-level matching. Ko Y; Song S; Baek J; Shim H Med Phys; 2024 Jun; 51(6):4181-4200. PubMed ID: 38478305 [TBL] [Abstract][Full Text] [Related]
10. 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]
11. Degradation Adaption Local-to-Global Transformer for Low-Dose CT Image Denoising. Wang H; Chi J; Wu C; Yu X; Wu H J Digit Imaging; 2023 Aug; 36(4):1894-1909. PubMed ID: 37118101 [TBL] [Abstract][Full Text] [Related]
12. A Review of deep learning methods for denoising of medical low-dose CT images. Zhang J; Gong W; Ye L; Wang F; Shangguan Z; Cheng Y Comput Biol Med; 2024 Mar; 171():108112. PubMed ID: 38387380 [TBL] [Abstract][Full Text] [Related]
13. Self-adaption and texture generation: A hybrid loss function for low-dose CT denoising. Wang Z; Liu M; Cheng X; Zhu J; Wang X; Gong H; Liu M; Xu L J Appl Clin Med Phys; 2023 Sep; 24(9):e14113. PubMed ID: 37571834 [TBL] [Abstract][Full Text] [Related]
14. X-ray CT image denoising with MINF: A modularized iterative network framework for data from multiple dose levels. Du Q; Tang Y; Wang J; Hou X; Wu Z; Li M; Yang X; Zheng J Comput Biol Med; 2023 Jan; 152():106419. PubMed ID: 36527781 [TBL] [Abstract][Full Text] [Related]
15. Domain-adaptive denoising network for low-dose CT via noise estimation and transfer learning. Wang J; Tang Y; Wu Z; Tsui BMW; Chen W; Yang X; Zheng J; Li M Med Phys; 2023 Jan; 50(1):74-88. PubMed ID: 36018732 [TBL] [Abstract][Full Text] [Related]
16. Total-body low-dose CT image denoising using a prior knowledge transfer technique with a contrastive regularization mechanism. Fu M; Duan Y; Cheng Z; Qin W; Wang Y; Liang D; Hu Z Med Phys; 2023 May; 50(5):2971-2984. PubMed ID: 36542423 [TBL] [Abstract][Full Text] [Related]
17. Low-Dose CT Image Denoising Based on Improved DD-Net and Local Filtered Mechanism. Liu H; Jin X; Liu L; Jin X Comput Intell Neurosci; 2022; 2022():2692301. PubMed ID: 35965772 [TBL] [Abstract][Full Text] [Related]
18. A densely connected LDCT image denoising network based on dual-edge extraction and multi-scale attention under compound loss. Lina J; Xu H; Aimin H; Beibei J; Zhiguo G J Xray Sci Technol; 2023; 31(6):1207-1226. PubMed ID: 37742690 [TBL] [Abstract][Full Text] [Related]
19. Multi-scale feature aggregation and fusion network with self-supervised multi-level perceptual loss for textures preserving low-dose CT denoising. Zhang Y; Wan Z; Wang D; Meng J; Ma F; Guo Y; Liu J; Li G; Liu Y Phys Med Biol; 2024 Apr; 69(10):. PubMed ID: 38593821 [No Abstract] [Full Text] [Related]
20. Compound feature attention network with edge enhancement for low-dose CT denoising. Wang S; Liu Y; Zhang P; Chen P; Li Z; Yan R; Li S; Hou R; Gui Z J Xray Sci Technol; 2023; 31(5):915-933. PubMed ID: 37355934 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]