158 related articles for article (PubMed ID: 26561284)
1. Extracting Information From Previous Full-Dose CT Scan for Knowledge-Based Bayesian Reconstruction of Current Low-Dose CT Images.
Zhang H; Han H; Liang Z; Hu Y; Liu Y; Moore W; Ma J; Lu H
IEEE Trans Med Imaging; 2016 Mar; 35(3):860-70. PubMed ID: 26561284
[TBL] [Abstract][Full Text] [Related]
2. A Feasibility Study of Extracting Tissue Textures From a Previous Full-Dose CT Database as Prior Knowledge for Bayesian Reconstruction of Current Low-Dose CT Images.
Gao Y; Liang Z; Moore W; Zhang H; Pomeroy MJ; Ferretti JA; Bilfinger TV; Ma J; Lu H
IEEE Trans Med Imaging; 2019 Aug; 38(8):1981-1992. PubMed ID: 30605098
[TBL] [Abstract][Full Text] [Related]
3. Machine Learned Texture Prior From Full-Dose CT Database via Multi-Modality Feature Selection for Bayesian Reconstruction of Low-Dose CT.
Gao Y; Tan J; Shi Y; Zhang H; Lu S; Gupta A; Li H; Reiter M; Liang Z
IEEE Trans Med Imaging; 2023 Nov; 42(11):3129-3139. PubMed ID: 34968178
[TBL] [Abstract][Full Text] [Related]
4. Deriving adaptive MRF coefficients from previous normal-dose CT scan for low-dose image reconstruction via penalized weighted least-squares minimization.
Zhang H; Han H; Wang J; Ma J; Liu Y; Moore W; Liang Z
Med Phys; 2014 Apr; 41(4):041916. PubMed ID: 24694147
[TBL] [Abstract][Full Text] [Related]
5. Characterization of tissue-specific pre-log Bayesian CT reconstruction by texture-dose relationship.
Gao Y; Liang Z; Xing Y; Zhang H; Pomeroy M; Lu S; Ma J; Lu H; Moore W
Med Phys; 2020 Oct; 47(10):5032-5047. PubMed ID: 32786070
[TBL] [Abstract][Full Text] [Related]
6. Statistical CT reconstruction using region-aware texture preserving regularization learning from prior normal-dose CT image.
Jia X; Liao Y; Zeng D; Zhang H; Zhang Y; He J; Bian Z; Wang Y; Tao X; Liang Z; Huang J; Ma J
Phys Med Biol; 2018 Nov; 63(22):225020. PubMed ID: 30457116
[TBL] [Abstract][Full Text] [Related]
7. Spectral CT Reconstruction via Low-Rank Representation and Region-Specific Texture Preserving Markov Random Field Regularization.
Shi Y; Gao Y; Zhang Y; Sun J; Mou X; Liang Z
IEEE Trans Med Imaging; 2020 Oct; 39(10):2996-3007. PubMed ID: 32217474
[TBL] [Abstract][Full Text] [Related]
8. Low-Dose Lung CT Image Restoration Using Adaptive Prior Features From Full-Dose Training Database.
Zhang Y; Rong J; Lu H; Xing Y; Meng J
IEEE Trans Med Imaging; 2017 Dec; 36(12):2510-2523. PubMed ID: 28961108
[TBL] [Abstract][Full Text] [Related]
9. Assessment of prior image induced nonlocal means regularization for low-dose CT reconstruction: Change in anatomy.
Zhang H; Ma J; Wang J; Moore W; Liang Z
Med Phys; 2017 Sep; 44(9):e264-e278. PubMed ID: 28901622
[TBL] [Abstract][Full Text] [Related]
10. Model-based iterative reconstruction technique for ultralow-dose computed tomography of the lung: a pilot study.
Yamada Y; Jinzaki M; Tanami Y; Shiomi E; Sugiura H; Abe T; Kuribayashi S
Invest Radiol; 2012 Aug; 47(8):482-9. PubMed ID: 22766910
[TBL] [Abstract][Full Text] [Related]
11. Constructing a tissue-specific texture prior by machine learning from previous full-dose scan for Bayesian reconstruction of current ultralow-dose CT images.
Gao Y; Tan J; Shi Y; Lu S; Gupta A; Li H; Liang Z
J Med Imaging (Bellingham); 2020 May; 7(3):032502. PubMed ID: 32118093
[No Abstract] [Full Text] [Related]
12. Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective.
Brady SL; Yee BS; Kaufman RA
Med Phys; 2012 Sep; 39(9):5520-31. PubMed ID: 22957619
[TBL] [Abstract][Full Text] [Related]
13. Radiation Dose Reduction in Computed Tomography-Guided Lung Interventions using an Iterative Reconstruction Technique.
Chang DH; Hiss S; Mueller D; Hellmich M; Borggrefe J; Bunck AC; Maintz D; Hackenbroch M
Rofo; 2015 Oct; 187(10):906-14. PubMed ID: 26085175
[TBL] [Abstract][Full Text] [Related]
14. Optimizing a Parameterized Plug-and-Play ADMM for Iterative Low-Dose CT Reconstruction.
He J; Yang Y; Wang Y; Zeng D; Bian Z; Zhang H; Sun J; Xu Z; Ma J
IEEE Trans Med Imaging; 2019 Feb; 38(2):371-382. PubMed ID: 30106717
[TBL] [Abstract][Full Text] [Related]
15. A Task-dependent Investigation on Dose and Texture in CT Image Reconstruction.
Gao Y; Liang Z; Zhang H; Yang J; Ferretti J; Bilfinger T; Yaddanapudi K; Schweitzer M; Bhattacharji P; Moore W
IEEE Trans Radiat Plasma Med Sci; 2020 Jul; 4(4):441-449. PubMed ID: 33907724
[TBL] [Abstract][Full Text] [Related]
16. Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization.
Dong X; Niu T; Zhu L
Med Phys; 2014 May; 41(5):051909. PubMed ID: 24784388
[TBL] [Abstract][Full Text] [Related]
17. Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction.
Xiong L; Li N; Qiu W; Luo Y; Li Y; Zhang Y
Med Biol Eng Comput; 2024 Mar; 62(3):701-712. PubMed ID: 37982956
[TBL] [Abstract][Full Text] [Related]
18. Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.
Solomon J; Mileto A; Nelson RC; Roy Choudhury K; Samei E
Radiology; 2016 Apr; 279(1):185-94. PubMed ID: 26624973
[TBL] [Abstract][Full Text] [Related]
19. Texture-aware dual domain mapping model for low-dose CT reconstruction.
Wang H; Zhao X; Liu W; Li LC; Ma J; Guo L
Med Phys; 2022 Jun; 49(6):3860-3873. PubMed ID: 35297051
[TBL] [Abstract][Full Text] [Related]
20. Efficient low-dose CT artifact mitigation using an artifact-matched prior scan.
Xu W; Mueller K
Med Phys; 2012 Aug; 39(8):4748-60. PubMed ID: 22894400
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]