127 related articles for article (PubMed ID: 37546774)
1. Enhanced cell segmentation with limited annotated data using generative adversarial networks.
Zargari A; Mashhadi N; Shariati SA
bioRxiv; 2023 Jul; ():. PubMed ID: 37546774
[TBL] [Abstract][Full Text] [Related]
2. Enhanced cell segmentation with limited training datasets using cycle generative adversarial networks.
Zargari A; Topacio BR; Mashhadi N; Shariati SA
iScience; 2024 May; 27(5):109740. PubMed ID: 38706861
[TBL] [Abstract][Full Text] [Related]
3. Active Cell Appearance Model Induced Generative Adversarial Networks for Annotation-Efficient Cell Segmentation and Identification on Adaptive Optics Retinal Images.
Liu J; Shen C; Aguilera N; Cukras C; Hufnagel RB; Zein WM; Liu T; Tam J
IEEE Trans Med Imaging; 2021 Oct; 40(10):2820-2831. PubMed ID: 33507868
[TBL] [Abstract][Full Text] [Related]
4. Synthetic Generation of 3D Microscopy Images using Generative Adversarial Networks.
Narotamo H; Ouarne M; Franco CA; Silveira M
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():549-552. PubMed ID: 36086569
[TBL] [Abstract][Full Text] [Related]
5. Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks.
Sandfort V; Yan K; Pickhardt PJ; Summers RM
Sci Rep; 2019 Nov; 9(1):16884. PubMed ID: 31729403
[TBL] [Abstract][Full Text] [Related]
6. Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review.
Ali H; Shah Z
JMIR Med Inform; 2022 Jun; 10(6):e37365. PubMed ID: 35709336
[TBL] [Abstract][Full Text] [Related]
7. Cross-modality deep learning: Contouring of MRI data from annotated CT data only.
Kieselmann JP; Fuller CD; Gurney-Champion OJ; Oelfke U
Med Phys; 2021 Apr; 48(4):1673-1684. PubMed ID: 33251619
[TBL] [Abstract][Full Text] [Related]
8. Generative Adversarial Networks in Digital Histopathology: Current Applications, Limitations, Ethical Considerations, and Future Directions.
Alajaji SA; Khoury ZH; Elgharib M; Saeed M; Ahmed ARH; Khan MB; Tavares T; Jessri M; Puche AC; Hoorfar H; Stojanov I; Sciubba JJ; Sultan AS
Mod Pathol; 2024 Jan; 37(1):100369. PubMed ID: 37890670
[TBL] [Abstract][Full Text] [Related]
9. Using deep learning to generate synthetic B-mode musculoskeletal ultrasound images.
Cronin NJ; Finni T; Seynnes O
Comput Methods Programs Biomed; 2020 Nov; 196():105583. PubMed ID: 32544777
[TBL] [Abstract][Full Text] [Related]
10. Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models.
Usman Akbar M; Larsson M; Blystad I; Eklund A
Sci Data; 2024 Feb; 11(1):259. PubMed ID: 38424097
[TBL] [Abstract][Full Text] [Related]
11. Compensation cycle consistent generative adversarial networks (Comp-GAN) for synthetic CT generation from MR scans with truncated anatomy.
Zhao Y; Wang H; Yu C; Court LE; Wang X; Wang Q; Pan T; Ding Y; Phan J; Yang J
Med Phys; 2023 Jul; 50(7):4399-4414. PubMed ID: 36698291
[TBL] [Abstract][Full Text] [Related]
12. SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing.
Bargsten L; Schlaefer A
Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1427-1436. PubMed ID: 32556953
[TBL] [Abstract][Full Text] [Related]
13. A survey on generative adversarial networks for imbalance problems in computer vision tasks.
Sampath V; Maurtua I; Aguilar MartÃn JJ; Gutierrez A
J Big Data; 2021; 8(1):27. PubMed ID: 33552840
[TBL] [Abstract][Full Text] [Related]
14. Self-Supervised Segmentation of 3D Fluorescence Microscopy Images Using CycleGAN.
Rosa A; Narotamo H; Silveira M
Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083101
[TBL] [Abstract][Full Text] [Related]
15. Generative Adversarial Networks Can Create High Quality Artificial Prostate Cancer Magnetic Resonance Images.
Xu IRL; Van Booven DJ; Goberdhan S; Breto A; Porto J; Alhusseini M; Algohary A; Stoyanova R; Punnen S; Mahne A; Arora H
J Pers Med; 2023 Mar; 13(3):. PubMed ID: 36983728
[TBL] [Abstract][Full Text] [Related]
16. Label-informed cardiac magnetic resonance image synthesis through conditional generative adversarial networks.
Amirrajab S; Al Khalil Y; Lorenz C; Weese J; Pluim J; Breeuwer M
Comput Med Imaging Graph; 2022 Oct; 101():102123. PubMed ID: 36174308
[TBL] [Abstract][Full Text] [Related]
17. High resolution histopathology image generation and segmentation through adversarial training.
Li W; Li J; Polson J; Wang Z; Speier W; Arnold C
Med Image Anal; 2022 Jan; 75():102251. PubMed ID: 34814059
[TBL] [Abstract][Full Text] [Related]
18. Generating Synthetic Labeled Data From Existing Anatomical Models: An Example With Echocardiography Segmentation.
Gilbert A; Marciniak M; Rodero C; Lamata P; Samset E; Mcleod K
IEEE Trans Med Imaging; 2021 Oct; 40(10):2783-2794. PubMed ID: 33444134
[TBL] [Abstract][Full Text] [Related]
19. Style Transfer-assisted Deep Learning Method for Kidney Segmentation at Multiphase MRI.
Guo J; Goyal M; Xi Y; Hinojosa L; Haddad G; Albayrak E; Pedrosa I
Radiol Artif Intell; 2023 Nov; 5(6):e230043. PubMed ID: 38074795
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]
