522 related articles for article (PubMed ID: 29950012)
1. DLBI: deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy.
Li Y; Xu F; Zhang F; Xu P; Zhang M; Fan M; Li L; Gao X; Han R
Bioinformatics; 2018 Jul; 34(13):i284-i294. PubMed ID: 29950012
[TBL] [Abstract][Full Text] [Related]
2. nanoTRON: a Picasso module for MLP-based classification of super-resolution data.
Auer A; Strauss MT; Strauss S; Jungmann R
Bioinformatics; 2020 Jun; 36(11):3620-3622. PubMed ID: 32145010
[TBL] [Abstract][Full Text] [Related]
3. Deep-learning method for data association in particle tracking.
Yao Y; Smal I; Grigoriev I; Akhmanova A; Meijering E
Bioinformatics; 2020 Dec; 36(19):4935-4941. PubMed ID: 32879934
[TBL] [Abstract][Full Text] [Related]
4. Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences.
Kefer P; Iqbal F; Locatelli M; Lawrimore J; Zhang M; Bloom K; Bonin K; Vidi PA; Liu J
Mol Biol Cell; 2021 Apr; 32(9):903-914. PubMed ID: 33502895
[TBL] [Abstract][Full Text] [Related]
5. Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning.
Du C; Du C; Huang L; He H
IEEE Trans Neural Netw Learn Syst; 2019 Aug; 30(8):2310-2323. PubMed ID: 30561354
[TBL] [Abstract][Full Text] [Related]
6. Advancing biological super-resolution microscopy through deep learning: a brief review.
Yang T; Luo Y; Ji W; Yang G
Biophys Rep; 2021 Aug; 7(4):253-266. PubMed ID: 37287757
[TBL] [Abstract][Full Text] [Related]
7. BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images.
Scherr T; Streule K; Bartschat A; Böhland M; Stegmaier J; Reischl M; Orian-Rousseau V; Mikut R
Bioinformatics; 2020 Nov; 36(17):4668-4670. PubMed ID: 32589734
[TBL] [Abstract][Full Text] [Related]
8. DETECTOR: structural information guided artifact detection for super-resolution fluorescence microscopy image.
Gao S; Xu F; Li H; Xue F; Zhang M; Xu P; Zhang F
Biomed Opt Express; 2021 Sep; 12(9):5751-5769. PubMed ID: 34692213
[TBL] [Abstract][Full Text] [Related]
9. Parametric comparison between sparsity-based and deep learning-based image reconstruction of super-resolution fluorescence microscopy.
Chen J; Chen Y
Biomed Opt Express; 2021 Aug; 12(8):5246-5260. PubMed ID: 34513254
[TBL] [Abstract][Full Text] [Related]
10. Efficient super-resolution volumetric imaging by radial fluctuation Bayesian analysis light-sheet microscopy.
Chen R; Zhao Y; Li M; Wang Y; Zhang L; Fei P
J Biophotonics; 2020 Aug; 13(8):e201960242. PubMed ID: 32314491
[TBL] [Abstract][Full Text] [Related]
11. A survey on applications of deep learning in microscopy image analysis.
Liu Z; Jin L; Chen J; Fang Q; Ablameyko S; Yin Z; Xu Y
Comput Biol Med; 2021 Jul; 134():104523. PubMed ID: 34091383
[TBL] [Abstract][Full Text] [Related]
12. BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference.
Li H; Shen C; Wang G; Sun Q; Yu K; Li Z; Liang X; Chen R; Wu H; Wang F; Wang Z; Lian C
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36572655
[TBL] [Abstract][Full Text] [Related]
13. Deep Unsupervised Fusion Learning for Hyperspectral Image Super Resolution.
Liu Z; Zheng Y; Han XH
Sensors (Basel); 2021 Mar; 21(7):. PubMed ID: 33800532
[TBL] [Abstract][Full Text] [Related]
14. DL-MRI: A Unified Framework of Deep Learning-Based MRI Super Resolution.
Liu H; Liu J; Li J; Pan JS; Yu X
J Healthc Eng; 2021; 2021():5594649. PubMed ID: 33897991
[TBL] [Abstract][Full Text] [Related]
15. Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy.
Park H; Na M; Kim B; Park S; Kim KH; Chang S; Ye JC
Nat Commun; 2022 Jun; 13(1):3297. PubMed ID: 35676288
[TBL] [Abstract][Full Text] [Related]
16. DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples.
Wodzinski M; Müller H
Comput Methods Programs Biomed; 2021 Jan; 198():105799. PubMed ID: 33137701
[TBL] [Abstract][Full Text] [Related]
17. Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction.
Belthangady C; Royer LA
Nat Methods; 2019 Dec; 16(12):1215-1225. PubMed ID: 31285623
[TBL] [Abstract][Full Text] [Related]
18. Super-Resolution Ultrasound Localization Microscopy Through Deep Learning.
van Sloun RJG; Solomon O; Bruce M; Khaing ZZ; Wijkstra H; Eldar YC; Mischi M
IEEE Trans Med Imaging; 2021 Mar; 40(3):829-839. PubMed ID: 33180723
[TBL] [Abstract][Full Text] [Related]
19. Exploit Camera Raw Data for Video Super- Resolution via Hidden Markov Model Inference.
Liu X; Shi K; Wang Z; Chen J
IEEE Trans Image Process; 2021; 30():2127-2140. PubMed ID: 33439845
[TBL] [Abstract][Full Text] [Related]
20. Exploring generative deep learning for omics data using log-linear models.
Hess M; Hackenberg M; Binder H
Bioinformatics; 2020 Dec; 36(20):5045-5053. PubMed ID: 32647888
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
