BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

241 related articles for article (PubMed ID: 31970879)

  • 1. Optical coherence tomography image denoising using a generative adversarial network with speckle modulation.
    Dong Z; Liu G; Ni G; Jerwick J; Duan L; Zhou C
    J Biophotonics; 2020 Apr; 13(4):e201960135. PubMed ID: 31970879
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SiameseGAN: A Generative Model for Denoising of Spectral Domain Optical Coherence Tomography Images.
    Kande NA; Dakhane R; Dukkipati A; Yalavarthy PK
    IEEE Trans Med Imaging; 2021 Jan; 40(1):180-192. PubMed ID: 32924938
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Multi-task generative adversarial network for retinal optical coherence tomography image denoising.
    Xie Q; Ma Z; Zhu L; Fan F; Meng X; Gao X; Zhu J
    Phys Med Biol; 2023 Feb; 68(4):. PubMed ID: 36137542
    [No Abstract]   [Full Text] [Related]  

  • 4. Comparative study of deep neural networks with unsupervised Noise2Noise strategy for noise reduction of optical coherence tomography images.
    Qiu B; Zeng S; Meng X; Jiang Z; You Y; Geng M; Li Z; Hu Y; Huang Z; Zhou C; Ren Q; Lu Y
    J Biophotonics; 2021 Nov; 14(11):e202100151. PubMed ID: 34383390
    [TBL] [Abstract][Full Text] [Related]  

  • 5. DHNet: High-resolution and hierarchical network for cross-domain OCT speckle noise reduction.
    Zhou Y; Li J; Wang M; Peng Y; Chen Z; Zhu W; Shi F; Wang L; Wang T; Yao C; Chen X
    Med Phys; 2022 Sep; 49(9):5914-5928. PubMed ID: 35611567
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Speckle Noise Reduction for OCT Images Based on Image Style Transfer and Conditional GAN.
    Zhou Y; Yu K; Wang M; Ma Y; Peng Y; Chen Z; Zhu W; Shi F; Chen X
    IEEE J Biomed Health Inform; 2022 Jan; 26(1):139-150. PubMed ID: 33882009
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Semi-Supervised Capsule cGAN for Speckle Noise Reduction in Retinal OCT Images.
    Wang M; Zhu W; Yu K; Chen Z; Shi F; Zhou Y; Ma Y; Peng Y; Bao D; Feng S; Ye L; Xiang D; Chen X
    IEEE Trans Med Imaging; 2021 Apr; 40(4):1168-1183. PubMed ID: 33395391
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Deep feature loss to denoise OCT images using deep neural networks.
    Mehdizadeh M; MacNish C; Xiao D; Alonso-Caneiro D; Kugelman J; Bennamoun M
    J Biomed Opt; 2021 Apr; 26(4):. PubMed ID: 33893726
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Super-resolution technology to simultaneously improve optical & digital resolution of optical coherence tomography via deep learning.
    Cao S; Yao X; Koirala N; Brott B; Litovsky S; Ling Y; Gan Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1879-1882. PubMed ID: 33018367
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multiscale denoising generative adversarial network for speckle reduction in optical coherence tomography images.
    Yu X; Ge C; Li M; Aziz MZ; Mo J; Fan Z
    J Med Imaging (Bellingham); 2023 Mar; 10(2):024006. PubMed ID: 37009058
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Sm-Net OCT: a deep-learning-based speckle-modulating optical coherence tomography.
    Ni G; Chen Y; Wu R; Wang X; Zeng M; Liu Y
    Opt Express; 2021 Aug; 29(16):25511-25523. PubMed ID: 34614881
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hybrid-structure network and network comparative study for deep-learning-based speckle-modulating optical coherence tomography.
    Ni G; Wu R; Zhong J; Chen Y; Wan L; Xie Y; Mei J; Liu Y
    Opt Express; 2022 May; 30(11):18919-18938. PubMed ID: 36221682
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders.
    Zheng C; Xie X; Zhou K; Chen B; Chen J; Ye H; Li W; Qiao T; Gao S; Yang J; Liu J
    Transl Vis Sci Technol; 2020 May; 9(2):29. PubMed ID: 32832202
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Retinal fundus image superresolution generated by optical coherence tomography based on a realistic mixed attention GAN.
    Tian C; Yang J; Li P; Zhang S; Mi S
    Med Phys; 2022 May; 49(5):3185-3198. PubMed ID: 35238048
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Reducing speckle in anterior segment optical coherence tomography images based on a convolutional neural network.
    Liu L; Zhai Z; Zhang T; Fan L
    Appl Opt; 2021 Dec; 60(35):10964-10974. PubMed ID: 35200859
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Simultaneous denoising and super-resolution of optical coherence tomography images based on generative adversarial network.
    Huang Y; Lu Z; Shao Z; Ran M; Zhou J; Fang L; Zhang Y
    Opt Express; 2019 Apr; 27(9):12289-12307. PubMed ID: 31052772
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Retinal optical coherence tomography image enhancement via deep learning.
    Halupka KJ; Antony BJ; Lee MH; Lucy KA; Rai RS; Ishikawa H; Wollstein G; Schuman JS; Garnavi R
    Biomed Opt Express; 2018 Dec; 9(12):6205-6221. PubMed ID: 31065423
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Toward Ground-Truth Optical Coherence Tomography via Three-Dimensional Unsupervised Deep Learning Processing and Data.
    Ni G; Wu R; Zheng F; Li M; Huang S; Ge X; Liu L; Liu Y
    IEEE Trans Med Imaging; 2024 Jun; 43(6):2395-2407. PubMed ID: 38324426
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 13.