117 related articles for article (PubMed ID: 37333366)
21. Deep learning with noise-to-noise training for denoising in SPECT myocardial perfusion imaging.
Liu J; Yang Y; Wernick MN; Pretorius PH; King MA
Med Phys; 2021 Jan; 48(1):156-168. PubMed ID: 33145782
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. An approach to analyze the breast tissues in infrared images using nonlinear adaptive level sets and Riesz transform features.
Prabha S; Suganthi SS; Sujatha CM
Technol Health Care; 2015; 23(4):429-42. PubMed ID: 26409908
[TBL] [Abstract][Full Text] [Related]
24. Denoising Tc-99m DMSA images using Denoising Convolutional Neural Network with comparison to a Block Matching Filter.
Chaudhary J; Phulia A; Pandey AK; Sharma PD; Patel C
Nucl Med Commun; 2023 Aug; 44(8):682-690. PubMed ID: 37272279
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions.
Polleys CM; Singh P; Thieu HT; Genega EM; Jahanseir N; Zuckerman AL; Díaz FR; Patra A; Beheshti A; Georgakoudi I
bioRxiv; 2024 May; ():. PubMed ID: 38798665
[TBL] [Abstract][Full Text] [Related]
27. Real-time denoising of ultrasound images based on deep learning.
Cammarasana S; Nicolardi P; Patanè G
Med Biol Eng Comput; 2022 Aug; 60(8):2229-2244. PubMed ID: 35672630
[TBL] [Abstract][Full Text] [Related]
28. Denoising of PET images by combining wavelets and curvelets for improved preservation of resolution and quantitation.
Le Pogam A; Hanzouli H; Hatt M; Cheze Le Rest C; Visvikis D
Med Image Anal; 2013 Dec; 17(8):877-91. PubMed ID: 23837964
[TBL] [Abstract][Full Text] [Related]
29. Complex denoising of MR data via wavelet analysis: application for functional MRI.
Zaroubi S; Goelman G
Magn Reson Imaging; 2000 Jan; 18(1):59-68. PubMed ID: 10642103
[TBL] [Abstract][Full Text] [Related]
30. 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]
31. Hybrid deep-learning-based denoising method for compressed sensing in pituitary MRI: comparison with the conventional wavelet-based denoising method.
Uetani H; Nakaura T; Kitajima M; Morita K; Haraoka K; Shinojima N; Tateishi M; Inoue T; Sasao A; Mukasa A; Azuma M; Ikeda O; Yamashita Y; Hirai T
Eur Radiol; 2022 Jul; 32(7):4527-4536. PubMed ID: 35169896
[TBL] [Abstract][Full Text] [Related]
32. Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data.
Shah ZH; Müller M; Hübner W; Wang TC; Telman D; Huser T; Schenck W
Gigascience; 2024 Jan; 13():. PubMed ID: 38217407
[TBL] [Abstract][Full Text] [Related]
33. [A diffusion-weighted image denoising algorithm using HOSVD combined with Rician noise corrected model].
Xu P; Guo L; Feng Y; Zhang X
Nan Fang Yi Ke Da Xue Xue Bao; 2021 Aug; 41(9):1400-1408. PubMed ID: 34658356
[TBL] [Abstract][Full Text] [Related]
34. Deep Learning Denoising of Low-Dose Computed Tomography Chest Images: A Quantitative and Qualitative Image Analysis.
Azour L; Hu Y; Ko JP; Chen B; Knoll F; Alpert JB; Brusca-Augello G; Mason DM; Wickstrom ML; Kwon YJF; Babb J; Liang Z; Moore WH
J Comput Assist Tomogr; 2023 Mar-Apr 01; 47(2):212-219. PubMed ID: 36790870
[TBL] [Abstract][Full Text] [Related]
35. A wavelet-based method for MRI liver image denoising.
Ali MN
Biomed Tech (Berl); 2019 Dec; 64(6):699-709. PubMed ID: 31145685
[TBL] [Abstract][Full Text] [Related]
36. Dual tree complex wavelet transform based denoising of optical microscopy images.
Bal U
Biomed Opt Express; 2012 Dec; 3(12):3231-9. PubMed ID: 23243573
[TBL] [Abstract][Full Text] [Related]
37. 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]
38. Diagnostic Performance in Low- and High-Contrast Tasks of an Image-Based Denoising Algorithm Applied to Radiation Dose-Reduced Multiphase Abdominal CT Examinations.
Inoue A; Voss BA; Lee NJ; Takahashi H; Kozaka K; Heiken JP; Ehman EC; Vasconcelos R; Fidler JL; Lee YS; Mileto A; Johnson MP; Baer-Beck M; Weber NM; Michalak GJ; Halaweish A; Carter RE; McCollough CH; Fletcher JG
AJR Am J Roentgenol; 2023 Jan; 220(1):73-85. PubMed ID: 35731096
[No Abstract] [Full Text] [Related]
39. A wavelet multiscale denoising algorithm for magnetic resonance (MR) images.
Yang X; Fei B
Meas Sci Technol; 2011 Feb; 22(2):25803. PubMed ID: 23853425
[TBL] [Abstract][Full Text] [Related]
40. Recent developments in denoising medical images using deep learning: An overview of models, techniques, and challenges.
Nazir N; Sarwar A; Saini BS
Micron; 2024 May; 180():103615. PubMed ID: 38471391
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]