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.
718 related articles for article (PubMed ID: 32730661)
1. A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI. Bahrami A; Karimian A; Fatemizadeh E; Arabi H; Zaidi H Med Phys; 2020 Oct; 47(10):5158-5171. PubMed ID: 32730661 [TBL] [Abstract][Full Text] [Related]
2. Comparison of different deep learning architectures for synthetic CT generation from MR images. Bahrami A; Karimian A; Arabi H Phys Med; 2021 Oct; 90():99-107. PubMed ID: 34597891 [TBL] [Abstract][Full Text] [Related]
3. MR-based synthetic CT generation using a deep convolutional neural network method. Han X Med Phys; 2017 Apr; 44(4):1408-1419. PubMed ID: 28192624 [TBL] [Abstract][Full Text] [Related]
4. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging. Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353 [TBL] [Abstract][Full Text] [Related]
5. Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapy. Olberg S; Zhang H; Kennedy WR; Chun J; Rodriguez V; Zoberi I; Thomas MA; Kim JS; Mutic S; Green OL; Park JC Med Phys; 2019 Sep; 46(9):4135-4147. PubMed ID: 31309586 [TBL] [Abstract][Full Text] [Related]
6. Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients. Tie X; Lam SK; Zhang Y; Lee KH; Au KH; Cai J Med Phys; 2020 Apr; 47(4):1750-1762. PubMed ID: 32012292 [TBL] [Abstract][Full Text] [Related]
7. Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region. Arabi H; Dowling JA; Burgos N; Han X; Greer PB; Koutsouvelis N; Zaidi H Med Phys; 2018 Nov; 45(11):5218-5233. PubMed ID: 30216462 [TBL] [Abstract][Full Text] [Related]
8. Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based three-dimensional convolutional neural network. Dinkla AM; Florkow MC; Maspero M; Savenije MHF; Zijlstra F; Doornaert PAH; van Stralen M; Philippens MEP; van den Berg CAT; Seevinck PR Med Phys; 2019 Sep; 46(9):4095-4104. PubMed ID: 31206701 [TBL] [Abstract][Full Text] [Related]
9. Synthetic CT generation from MRI using 3D transformer-based denoising diffusion model. Pan S; Abouei E; Wynne J; Chang CW; Wang T; Qiu RLJ; Li Y; Peng J; Roper J; Patel P; Yu DS; Mao H; Yang X Med Phys; 2024 Apr; 51(4):2538-2548. PubMed ID: 38011588 [TBL] [Abstract][Full Text] [Related]
10. Comparison of deep learning synthesis of synthetic CTs using clinical MRI inputs. Massa HA; Johnson JM; McMillan AB Phys Med Biol; 2020 Dec; 65(23):23NT03. PubMed ID: 33120371 [TBL] [Abstract][Full Text] [Related]
11. Head and neck synthetic CT generated from ultra-low-dose cone-beam CT following Image Gently Protocol using deep neural network. Yuan N; Rao S; Chen Q; Sensoy L; Qi J; Rong Y Med Phys; 2022 May; 49(5):3263-3277. PubMed ID: 35229904 [TBL] [Abstract][Full Text] [Related]
12. Synthetic CT Generation Based on T2 Weighted MRI of Nasopharyngeal Carcinoma (NPC) Using a Deep Convolutional Neural Network (DCNN). Wang Y; Liu C; Zhang X; Deng W Front Oncol; 2019; 9():1333. PubMed ID: 31850218 [No Abstract] [Full Text] [Related]
13. MRI-only based synthetic CT generation using dense cycle consistent generative adversarial networks. Lei Y; Harms J; Wang T; Liu Y; Shu HK; Jani AB; Curran WJ; Mao H; Liu T; Yang X Med Phys; 2019 Aug; 46(8):3565-3581. PubMed ID: 31112304 [TBL] [Abstract][Full Text] [Related]
14. GAN for synthesizing CT from T2-weighted MRI data towards MR-guided radiation treatment. Ranjan A; Lalwani D; Misra R MAGMA; 2022 Jun; 35(3):449-457. PubMed ID: 34741702 [TBL] [Abstract][Full Text] [Related]
15. Deep learning-based convolutional neural network for intramodality brain MRI synthesis. Osman AFI; Tamam NM J Appl Clin Med Phys; 2022 Apr; 23(4):e13530. PubMed ID: 35044073 [TBL] [Abstract][Full Text] [Related]
16. Monte Carlo Dose Calculation Using MRI Based Synthetic CT Generated by Fully Convolutional Neural Network for Gamma Knife Radiosurgery. Yuan J; Fredman E; Jin JY; Choi S; Mansur D; Sloan A; Machtay M; Zheng Y Technol Cancer Res Treat; 2021; 20():15330338211046433. PubMed ID: 34632872 [TBL] [Abstract][Full Text] [Related]
17. Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network. Kaushik SS; Bylund M; Cozzini C; Shanbhag D; Petit SF; Wyatt JJ; Menzel MI; Pirkl C; Mehta B; Chauhan V; Chandrasekharan K; Jonsson J; Nyholm T; Wiesinger F; Menze B Phys Med Biol; 2023 Sep; 68(19):. PubMed ID: 37567235 [No Abstract] [Full Text] [Related]
18. Multimodality MRI synchronous construction based deep learning framework for MRI-guided radiotherapy synthetic CT generation. Zhou X; Cai W; Cai J; Xiao F; Qi M; Liu J; Zhou L; Li Y; Song T Comput Biol Med; 2023 Aug; 162():107054. PubMed ID: 37290389 [TBL] [Abstract][Full Text] [Related]
19. 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]
20. Deep-learning based fast and accurate 3D CT deformable image registration in lung cancer. Ding Y; Feng H; Yang Y; Holmes J; Liu Z; Liu D; Wong WW; Yu NY; Sio TT; Schild SE; Li B; Liu W Med Phys; 2023 Nov; 50(11):6864-6880. PubMed ID: 37289193 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]