189 related articles for article (PubMed ID: 36715853)
1. MRI image synthesis for fluid-attenuated inversion recovery and diffusion-weighted images with deep learning.
Kawahara D; Yoshimura H; Matsuura T; Saito A; Nagata Y
Phys Eng Sci Med; 2023 Mar; 46(1):313-323. PubMed ID: 36715853
[TBL] [Abstract][Full Text] [Related]
2. T1-weighted and T2-weighted MRI image synthesis with convolutional generative adversarial networks.
Kawahara D; Nagata Y
Rep Pract Oncol Radiother; 2021; 26(1):35-42. PubMed ID: 33948300
[TBL] [Abstract][Full Text] [Related]
3. Multimodal MRI synthesis using unified generative adversarial networks.
Dai X; Lei Y; Fu Y; Curran WJ; Liu T; Mao H; Yang X
Med Phys; 2020 Dec; 47(12):6343-6354. PubMed ID: 33053202
[TBL] [Abstract][Full Text] [Related]
4. Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model.
Conte GM; Weston AD; Vogelsang DC; Philbrick KA; Cai JC; Barbera M; Sanvito F; Lachance DH; Jenkins RB; Tobin WO; Eckel-Passow JE; Erickson BJ
Radiology; 2021 May; 299(2):313-323. PubMed ID: 33687284
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. High-fidelity direct contrast synthesis from magnetic resonance fingerprinting.
Wang K; Doneva M; Meineke J; Amthor T; Karasan E; Tan F; Tamir JI; Yu SX; Lustig M
Magn Reson Med; 2023 Nov; 90(5):2116-2129. PubMed ID: 37332200
[TBL] [Abstract][Full Text] [Related]
8. High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN).
Li Z; Tian Q; Ngamsombat C; Cartmell S; Conklin J; Filho ALMG; Lo WC; Wang G; Ying K; Setsompop K; Fan Q; Bilgic B; Cauley S; Huang SY
Med Phys; 2022 Feb; 49(2):1000-1014. PubMed ID: 34961944
[TBL] [Abstract][Full Text] [Related]
9. Synthesizing high-resolution magnetic resonance imaging using parallel cycle-consistent generative adversarial networks for fast magnetic resonance imaging.
Xie H; Lei Y; Wang T; Roper J; Dhabaan AH; Bradley JD; Liu T; Mao H; Yang X
Med Phys; 2022 Jan; 49(1):357-369. PubMed ID: 34821395
[TBL] [Abstract][Full Text] [Related]
10. Conditional generative adversarial network for 3D rigid-body motion correction in MRI.
Johnson PM; Drangova M
Magn Reson Med; 2019 Sep; 82(3):901-910. PubMed ID: 31006909
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation.
Hagiwara A; Otsuka Y; Hori M; Tachibana Y; Yokoyama K; Fujita S; Andica C; Kamagata K; Irie R; Koshino S; Maekawa T; Chougar L; Wada A; Takemura MY; Hattori N; Aoki S
AJNR Am J Neuroradiol; 2019 Feb; 40(2):224-230. PubMed ID: 30630834
[TBL] [Abstract][Full Text] [Related]
13. Image synthesis of monoenergetic CT image in dual-energy CT using kilovoltage CT with deep convolutional generative adversarial networks.
Kawahara D; Ozawa S; Kimura T; Nagata Y
J Appl Clin Med Phys; 2021 Apr; 22(4):184-192. PubMed ID: 33599386
[TBL] [Abstract][Full Text] [Related]
14. Image synthesis with deep convolutional generative adversarial networks for material decomposition in dual-energy CT from a kilovoltage CT.
Kawahara D; Saito A; Ozawa S; Nagata Y
Comput Biol Med; 2021 Jan; 128():104111. PubMed ID: 33279790
[TBL] [Abstract][Full Text] [Related]
15. Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks.
Chan K; Maralani PJ; Moody AR; Khademi A
Front Neuroinform; 2023; 17():1197330. PubMed ID: 37603783
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers.
Kidoh M; Shinoda K; Kitajima M; Isogawa K; Nambu M; Uetani H; Morita K; Nakaura T; Tateishi M; Yamashita Y; Yamashita Y
Magn Reson Med Sci; 2020 Aug; 19(3):195-206. PubMed ID: 31484849
[TBL] [Abstract][Full Text] [Related]
18. Multi-sequence MR image-based synthetic CT generation using a generative adversarial network for head and neck MRI-only radiotherapy.
Qi M; Li Y; Wu A; Jia Q; Li B; Sun W; Dai Z; Lu X; Zhou L; Deng X; Song T
Med Phys; 2020 Apr; 47(4):1880-1894. PubMed ID: 32027027
[TBL] [Abstract][Full Text] [Related]
19. A deep learning approach for synthetic MRI based on two routine sequences and training with synthetic data.
Moya-Sáez E; Peña-Nogales Ó; Luis-García R; Alberola-López C
Comput Methods Programs Biomed; 2021 Oct; 210():106371. PubMed ID: 34525411
[TBL] [Abstract][Full Text] [Related]
20. Direct synthesis of multi-contrast brain MR images from MR multitasking spatial factors using deep learning.
Qiu S; Ma S; Wang L; Chen Y; Fan Z; Moser FG; Maya M; Sati P; Sicotte NL; Christodoulou AG; Xie Y; Li D
Magn Reson Med; 2023 Oct; 90(4):1672-1681. PubMed ID: 37246485
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
