BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

222 related articles for article (PubMed ID: 33395391)

  • 1. 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]  

  • 2. N2NSR-OCT: Simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning.
    Qiu B; You Y; Huang Z; Meng X; Jiang Z; Zhou C; Liu G; Yang K; Ren Q; Lu Y
    J Biophotonics; 2021 Jan; 14(1):e202000282. PubMed ID: 33025760
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. DeSpecNet: a CNN-based method for speckle reduction in retinal optical coherence tomography images.
    Shi F; Cai N; Gu Y; Hu D; Ma Y; Chen Y; Chen X
    Phys Med Biol; 2019 Sep; 64(17):175010. PubMed ID: 31342925
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN.
    Ma Y; Chen X; Zhu W; Cheng X; Xiang D; Shi F
    Biomed Opt Express; 2018 Nov; 9(11):5129-5146. PubMed ID: 30460118
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development and Clinical Validation of Semi-Supervised Generative Adversarial Networks for Detection of Retinal Disorders in Optical Coherence Tomography Images Using Small Dataset.
    Zheng C; Ye H; Yang J; Fei P; Qiu Y; Xie X; Wang Z; Chen J; Zhao P
    Asia Pac J Ophthalmol (Phila); 2022 May; 11(3):219-226. PubMed ID: 35342179
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Point based weakly semi-supervised biomarker detection with cross-scale and label assignment in retinal OCT images.
    Liu X; Zhu X; Zhang Y; Wang M
    Comput Methods Programs Biomed; 2024 Jun; 251():108229. PubMed ID: 38761413
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Texture preservation and speckle reduction in poor optical coherence tomography using the convolutional neural network.
    Xu M; Tang C; Hao F; Chen M; Lei Z
    Med Image Anal; 2020 Aug; 64():101727. PubMed ID: 32497871
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Semi-supervised contrast learning-based segmentation of choroidal vessel in optical coherence tomography images.
    Liu X; Pan J; Zhang Y; Li X; Tang J
    Phys Med Biol; 2023 Dec; 68(24):. PubMed ID: 37972415
    [No Abstract]   [Full Text] [Related]  

  • 10. 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]  

  • 11. Simultaneous alignment and surface regression using hybrid 2D-3D networks for 3D coherent layer segmentation of retinal OCT images with full and sparse annotations.
    Liu H; Wei D; Lu D; Tang X; Wang L; Zheng Y
    Med Image Anal; 2024 Jan; 91():103019. PubMed ID: 37944431
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Three-dimensional optical coherence tomography image denoising through multi-input fully-convolutional networks.
    Abbasi A; Monadjemi A; Fang L; Rabbani H; Zhang Y
    Comput Biol Med; 2019 May; 108():1-8. PubMed ID: 30901625
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Employing texture loss to denoise OCT images using generative adversarial networks.
    Mehdizadeh M; Saha S; Alonso-Caneiro D; Kugelman J; MacNish C; Chen F
    Biomed Opt Express; 2024 Apr; 15(4):2262-2280. PubMed ID: 38633090
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Semi-Supervised Learning for Low-Dose CT Image Restoration with Hierarchical Deep Generative Adversarial Network (HD-GAN).
    Choi K; Vania M; Kim S
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():2683-2686. PubMed ID: 31946448
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Learnable despeckling framework for optical coherence tomography images.
    Adabi S; Rashedi E; Clayton A; Mohebbi-Kalkhoran H; Chen XW; Conforto S; Nasiriavanaki M
    J Biomed Opt; 2018 Jan; 23(1):1-12. PubMed ID: 29368458
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Enhancement of OCT
    Yuan Z; Yang D; Zhao J; Liang Y
    Phys Med Biol; 2024 May; 69(11):. PubMed ID: 38749469
    [No Abstract]   [Full Text] [Related]  

  • 18. SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network.
    Li M; Hsu W; Xie X; Cong J; Gao W
    IEEE Trans Med Imaging; 2020 Jul; 39(7):2289-2301. PubMed ID: 31985412
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Spiking cortical model-based nonlocal means method for speckle reduction in optical coherence tomography images.
    Zhang X; Li L; Zhu F; Hou W; Chen X
    J Biomed Opt; 2014 Jun; 19(6):066005. PubMed ID: 24919448
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 12.