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Journal Abstract Search

350 related items for PubMed ID: 34038501

  • 1. Generative Adversarial Network Based Automatic Segmentation of Corneal Subbasal Nerves on In Vivo Confocal Microscopy Images.
    Yildiz E, Arslan AT, Yildiz Tas A, Acer AF, Demir S, Sahin A, Erol Barkana D.
    Transl Vis Sci Technol; 2021 May 03; 10(6):33. PubMed ID: 34038501
    [Abstract] [Full Text] [Related]

  • 2. A Deep Learning Model for Automated Sub-Basal Corneal Nerve Segmentation and Evaluation Using In Vivo Confocal Microscopy.
    Wei S, Shi F, Wang Y, Chou Y, Li X.
    Transl Vis Sci Technol; 2020 Jun 03; 9(2):32. PubMed ID: 32832205
    [Abstract] [Full Text] [Related]

  • 3. Segmentation and Evaluation of Corneal Nerves and Dendritic Cells From In Vivo Confocal Microscopy Images Using Deep Learning.
    Setu MAK, Schmidt S, Musial G, Stern ME, Steven P.
    Transl Vis Sci Technol; 2022 Jun 01; 11(6):24. PubMed ID: 35762938
    [Abstract] [Full Text] [Related]

  • 4. Combining In Vivo Corneal Confocal Microscopy With Deep Learning-Based Analysis Reveals Sensory Nerve Fiber Loss in Acute Simian Immunodeficiency Virus Infection.
    McCarron ME, Weinberg RL, Izzi JM, Queen SE, Tarwater PM, Misra SL, Russakoff DB, Oakley JD, Mankowski JL.
    Cornea; 2021 May 01; 40(5):635-642. PubMed ID: 33528225
    [Abstract] [Full Text] [Related]

  • 5. NerveStitcher: Corneal confocal microscope images stitching with neural networks.
    Li G, Li T, Li F, Zhang C.
    Comput Biol Med; 2022 Dec 01; 151(Pt B):106303. PubMed ID: 36435056
    [Abstract] [Full Text] [Related]

  • 6. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
    Tong N, Gou S, Yang S, Cao M, Sheng K.
    Med Phys; 2019 Jun 01; 46(6):2669-2682. PubMed ID: 31002188
    [Abstract] [Full Text] [Related]

  • 7. Open-Source Automated Segmentation of Neuronal Structures in Corneal Confocal Microscopy Images of the Subbasal Nerve Plexus With Accuracy on Par With Human Segmentation.
    Zemborain ZZ, Soifer M, Azar NS, Murillo S, Mousa HM, Perez VL, Farsiu S.
    Cornea; 2023 Oct 01; 42(10):1309-1319. PubMed ID: 37669422
    [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 01; 15(9):1427-1436. PubMed ID: 32556953
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  • 9. Comparative analysis of U-Net and TLMDB GAN for the cardiovascular segmentation of the ventricles in the heart.
    Zhang Y, Feng J, Guo X, Ren Y.
    Comput Methods Programs Biomed; 2022 Mar 01; 215():106614. PubMed ID: 35066315
    [Abstract] [Full Text] [Related]

  • 10. Fully automated montaging of laser scanning in vivo confocal microscopy images of the human corneal subbasal nerve plexus.
    Turuwhenua JT, Patel DV, McGhee CN.
    Invest Ophthalmol Vis Sci; 2012 Apr 24; 53(4):2235-42. PubMed ID: 22427563
    [Abstract] [Full Text] [Related]

  • 11. Automatic multiorgan segmentation in thorax CT images using U-net-GAN.
    Dong X, Lei Y, Wang T, Thomas M, Tang L, Curran WJ, Liu T, Yang X.
    Med Phys; 2019 May 24; 46(5):2157-2168. PubMed ID: 30810231
    [Abstract] [Full Text] [Related]

  • 12. Generative Adversarial Networks in Medical Image Processing.
    Gong M, Chen S, Chen Q, Zeng Y, Zhang Y.
    Curr Pharm Des; 2021 May 24; 27(15):1856-1868. PubMed ID: 33238866
    [Abstract] [Full Text] [Related]

  • 13. MSF-GAN: Multi-Scale Fuzzy Generative Adversarial Network for Breast Ultrasound Image Segmentation.
    Huang K, Zhang Y, Cheng HD, Xing P.
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov 24; 2021():3193-3196. PubMed ID: 34891920
    [Abstract] [Full Text] [Related]

  • 14. Automated fibroglandular tissue segmentation in breast MRI using generative adversarial networks.
    Ma X, Wang J, Zheng X, Liu Z, Long W, Zhang Y, Wei J, Lu Y.
    Phys Med Biol; 2020 May 19; 65(10):105006. PubMed ID: 32155611
    [Abstract] [Full Text] [Related]

  • 15. Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network.
    Han L, Huang Y, Dou H, Wang S, Ahamad S, Luo H, Liu Q, Fan J, Zhang J.
    Comput Methods Programs Biomed; 2020 Jun 19; 189():105275. PubMed ID: 31978805
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  • 16. Intensity non-uniformity correction in MR imaging using residual cycle generative adversarial network.
    Dai X, Lei Y, Liu Y, Wang T, Ren L, Curran WJ, Patel P, Liu T, Yang X.
    Phys Med Biol; 2020 Nov 27; 65(21):215025. PubMed ID: 33245059
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  • 17. A Hybrid System for Automatic Identification of Corneal Layers on In Vivo Confocal Microscopy Images.
    Tang N, Huang G, Lei D, Jiang L, Chen Q, He W, Tang F, Hong Y, Lv J, Qin Y, Lin Y, Lan Q, Qin Y, Lan R, Pan X, Li M, Xu F, Lu P.
    Transl Vis Sci Technol; 2023 Apr 03; 12(4):8. PubMed ID: 37026984
    [Abstract] [Full Text] [Related]

  • 18. SUSAN: segment unannotated image structure using adversarial network.
    Liu F.
    Magn Reson Med; 2019 May 03; 81(5):3330-3345. PubMed ID: 30536427
    [Abstract] [Full Text] [Related]

  • 19. Image generation by GAN and style transfer for agar plate image segmentation.
    Andreini P, Bonechi S, Bianchini M, Mecocci A, Scarselli F.
    Comput Methods Programs Biomed; 2020 Feb 03; 184():105268. PubMed ID: 31891902
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  • 20. Can Generative Adversarial Networks help to overcome the limited data problem in segmentation?
    Heilemann G, Matthewman M, Kuess P, Goldner G, Widder J, Georg D, Zimmermann L.
    Z Med Phys; 2022 Aug 03; 32(3):361-368. PubMed ID: 34930685
    [Abstract] [Full Text] [Related]

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