176 related articles for article (PubMed ID: 37820684)
21. Deep learning for fast denoising filtering in ultrasound localization microscopy.
Yu X; Luan S; Lei S; Huang J; Liu Z; Xue X; Ma T; Ding Y; Zhu B
Phys Med Biol; 2023 Oct; 68(20):. PubMed ID: 37703894
[No Abstract] [Full Text] [Related]
22. 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]
23. Ultralow-parameter denoising: Trainable bilateral filter layers in computed tomography.
Wagner F; Thies M; Gu M; Huang Y; Pechmann S; Patwari M; Ploner S; Aust O; Uderhardt S; Schett G; Christiansen S; Maier A
Med Phys; 2022 Aug; 49(8):5107-5120. PubMed ID: 35583171
[TBL] [Abstract][Full Text] [Related]
24. Dual-domain fusion deep convolutional neural network for low-dose CT denoising.
Li Z; Liu Y; Chen Y; Shu H; Lu J; Gui Z
J Xray Sci Technol; 2023; 31(4):757-775. PubMed ID: 37212059
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. 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]
27. High-field mr diffusion-weighted image denoising using a joint denoising convolutional neural network.
Wang H; Zheng R; Dai F; Wang Q; Wang C
J Magn Reson Imaging; 2019 Dec; 50(6):1937-1947. PubMed ID: 31012226
[TBL] [Abstract][Full Text] [Related]
28. 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]
29. Technical note: Phantom-based training framework for convolutional neural network CT noise reduction.
Huber NR; Missert AD; Gong H; Leng S; Yu L; McCollough CH
Med Phys; 2023 Feb; 50(2):821-830. PubMed ID: 36385704
[TBL] [Abstract][Full Text] [Related]
30. Improving phase-based conductivity reconstruction by means of deep learning-based denoising of
Jung KJ; Mandija S; Kim JH; Ryu K; Jung S; Cui C; Kim SY; Park M; van den Berg CAT; Kim DH
Magn Reson Med; 2021 Oct; 86(4):2084-2094. PubMed ID: 33949721
[TBL] [Abstract][Full Text] [Related]
31. 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]
32. Deep-learning-based denoising of X-ray differential phase and dark-field images.
Ren K; Gu Y; Luo M; Chen H; Wang Z
Eur J Radiol; 2023 Jun; 163():110835. PubMed ID: 37098281
[TBL] [Abstract][Full Text] [Related]
33. 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]
34. Edge-enhancement densenet for X-ray fluoroscopy image denoising in cardiac electrophysiology procedures.
Luo Y; Ma Y; O' Brien H; Jiang K; Kohli V; Maidelin S; Saeed M; Deng E; Pushparajah K; Rhode KS
Med Phys; 2022 Feb; 49(2):1262-1275. PubMed ID: 34954836
[TBL] [Abstract][Full Text] [Related]
35. Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising.
Tian Q; Zaretskaya N; Fan Q; Ngamsombat C; Bilgic B; Polimeni JR; Huang SY
Neuroimage; 2021 Jun; 233():117946. PubMed ID: 33711484
[TBL] [Abstract][Full Text] [Related]
36. Weakly-supervised progressive denoising with unpaired CT images.
Kim B; Shim H; Baek J
Med Image Anal; 2021 Jul; 71():102065. PubMed ID: 33915472
[TBL] [Abstract][Full Text] [Related]
37. [Progress in filters for denoising cryo-electron microscopy images].
Huang XR; Li S; Gao S
Beijing Da Xue Xue Bao Yi Xue Ban; 2021 Mar; 53(2):425-433. PubMed ID: 33879921
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. A denoising model based on multi-agent reinforcement learning with data transformation for digital tomosynthesis.
Nam K; Lee D; Lee S
Phys Med Biol; 2023 Jun; 68(12):. PubMed ID: 37192630
[No Abstract] [Full Text] [Related]
40. Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.
Zhu H; Tong D; Zhang L; Wang S; Wu W; Tang H; Chen Y; Luo L; Zhu J; Li B
Int J Comput Assist Radiol Surg; 2020 Feb; 15(2):193-201. PubMed ID: 31673961
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
