125 related articles for article (PubMed ID: 38478305)
1. 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]
2. 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]
3. 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]
4. Unsupervised low-dose CT denoising using bidirectional contrastive network.
Zhang Y; Zhang R; Cao R; Xu F; Jiang F; Meng J; Ma F; Guo Y; Liu J
Comput Methods Programs Biomed; 2024 Jun; 251():108206. PubMed ID: 38723435
[TBL] [Abstract][Full Text] [Related]
5. Probabilistic self-learning framework for low-dose CT denoising.
Bai T; Wang B; Nguyen D; Jiang S
Med Phys; 2021 May; 48(5):2258-2270. PubMed ID: 33621348
[TBL] [Abstract][Full Text] [Related]
6. Unpaired Low-Dose CT Denoising Network Based on Cycle-Consistent Generative Adversarial Network with Prior Image Information.
Tang C; Li J; Wang L; Li Z; Jiang L; Cai A; Zhang W; Liang N; Li L; Yan B
Comput Math Methods Med; 2019; 2019():8639825. PubMed ID: 31885686
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. 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]
10. 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]
11. 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]
12. Pediatric evaluations for deep learning CT denoising.
Nelson BJ; Kc P; Badal A; Jiang L; Masters SC; Zeng R
Med Phys; 2024 Feb; 51(2):978-990. PubMed ID: 38127330
[TBL] [Abstract][Full Text] [Related]
13. Utilization of an attentive map to preserve anatomical features for training convolutional neural-network-based low-dose CT denoiser.
Han M; Shim H; Baek J
Med Phys; 2023 May; 50(5):2787-2804. PubMed ID: 36734478
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Performance of a deep learning-based CT image denoising method: Generalizability over dose, reconstruction kernel, and slice thickness.
Zeng R; Lin CY; Li Q; Jiang L; Skopec M; Fessler JA; Myers KJ
Med Phys; 2022 Feb; 49(2):836-853. PubMed ID: 34954845
[TBL] [Abstract][Full Text] [Related]
16. A self-supervised guided knowledge distillation framework for unpaired low-dose CT image denoising.
Wang J; Tang Y; Wu Z; Du Q; Yao L; Yang X; Li M; Zheng J
Comput Med Imaging Graph; 2023 Jul; 107():102237. PubMed ID: 37116340
[TBL] [Abstract][Full Text] [Related]
17. HCformer: Hybrid CNN-Transformer for LDCT Image Denoising.
Yuan J; Zhou F; Guo Z; Li X; Yu H
J Digit Imaging; 2023 Oct; 36(5):2290-2305. PubMed ID: 37386333
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. Dose reduction and image enhancement in micro-CT using deep learning.
Muller FM; Maebe J; Vanhove C; Vandenberghe S
Med Phys; 2023 Sep; 50(9):5643-5656. PubMed ID: 36994779
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
