BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

149 related articles for article (PubMed ID: 32575396)

  • 1. Deep Learning of Cancer Stem Cell Morphology Using Conditional Generative Adversarial Networks.
    Aida S; Okugawa J; Fujisaka S; Kasai T; Kameda H; Sugiyama T
    Biomolecules; 2020 Jun; 10(6):. PubMed ID: 32575396
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning of Phase-Contrast Images of Cancer Stem Cells Using a Selected Dataset of High Accuracy Value Using Conditional Generative Adversarial Networks.
    Zhang Z; Ishihata H; Maruyama R; Kasai T; Kameda H; Sugiyama T
    Int J Mol Sci; 2023 Mar; 24(6):. PubMed ID: 36982398
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Temporal and Locational Values of Images Affecting the Deep Learning of Cancer Stem Cell Morphology.
    Hanai Y; Ishihata H; Zhang Z; Maruyama R; Kasai T; Kameda H; Sugiyama T
    Biomedicines; 2022 Apr; 10(5):. PubMed ID: 35625678
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep learning models for cancer stem cell detection: a brief review.
    Chen J; Xu L; Li X; Park S
    Front Immunol; 2023; 14():1214425. PubMed ID: 37441078
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multi-sequence MR image-based synthetic CT generation using a generative adversarial network for head and neck MRI-only radiotherapy.
    Qi M; Li Y; Wu A; Jia Q; Li B; Sun W; Dai Z; Lu X; Zhou L; Deng X; Song T
    Med Phys; 2020 Apr; 47(4):1880-1894. PubMed ID: 32027027
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Learning from adversarial medical images for X-ray breast mass segmentation.
    Shen T; Gou C; Wang FY; He Z; Chen W
    Comput Methods Programs Biomed; 2019 Oct; 180():105012. PubMed ID: 31421601
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Green Fluorescent Protein and Phase-Contrast Image Fusion via Generative Adversarial Networks.
    Tang W; Liu Y; Zhang C; Cheng J; Peng H; Chen X
    Comput Math Methods Med; 2019; 2019():5450373. PubMed ID: 31885682
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Conditional generative adversarial network for 3D rigid-body motion correction in MRI.
    Johnson PM; Drangova M
    Magn Reson Med; 2019 Sep; 82(3):901-910. PubMed ID: 31006909
    [TBL] [Abstract][Full Text] [Related]  

  • 9. SAP-cGAN: Adversarial learning for breast mass segmentation in digital mammogram based on superpixel average pooling.
    Li Y; Zhao G; Zhang Q; Lin Y; Wang M
    Med Phys; 2021 Mar; 48(3):1157-1167. PubMed ID: 33340125
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep learning detects genetic alterations in cancer histology generated by adversarial networks.
    Krause J; Grabsch HI; Kloor M; Jendrusch M; Echle A; Buelow RD; Boor P; Luedde T; Brinker TJ; Trautwein C; Pearson AT; Quirke P; Jenniskens J; Offermans K; van den Brandt PA; Kather JN
    J Pathol; 2021 May; 254(1):70-79. PubMed ID: 33565124
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning of Cancer Stem Cell Morphology.
    Kameda H; Ishihata H; Sugiyama T
    Methods Mol Biol; 2024; 2777():231-256. PubMed ID: 38478348
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose.
    Wang Y; Yu B; Wang L; Zu C; Lalush DS; Lin W; Wu X; Zhou J; Shen D; Zhou L
    Neuroimage; 2018 Jul; 174():550-562. PubMed ID: 29571715
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation.
    Hagiwara A; Otsuka Y; Hori M; Tachibana Y; Yokoyama K; Fujita S; Andica C; Kamagata K; Irie R; Koshino S; Maekawa T; Chougar L; Wada A; Takemura MY; Hattori N; Aoki S
    AJNR Am J Neuroradiol; 2019 Feb; 40(2):224-230. PubMed ID: 30630834
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis.
    Rana A; Lowe A; Lithgow M; Horback K; Janovitz T; Da Silva A; Tsai H; Shanmugam V; Bayat A; Shah P
    JAMA Netw Open; 2020 May; 3(5):e205111. PubMed ID: 32432709
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Virtual organelle self-coding for fluorescence imaging via adversarial learning.
    Nguyen T; Bui V; Thai A; Lam V; Raub C; Chang LC; Nehmetallah G
    J Biomed Opt; 2020 Sep; 25(9):. PubMed ID: 32996300
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Generative approach for data augmentation for deep learning-based bone surface segmentation from ultrasound images.
    Zaman A; Park SH; Bang H; Park CW; Park I; Joung S
    Int J Comput Assist Radiol Surg; 2020 Jun; 15(6):931-941. PubMed ID: 32399586
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Generative Adversarial Network for Medical Images (MI-GAN).
    Iqbal T; Ali H
    J Med Syst; 2018 Oct; 42(11):231. PubMed ID: 30315368
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Accurate colorectal tumor segmentation for CT scans based on the label assignment generative adversarial network.
    Liu X; Guo S; Zhang H; He K; Mu S; Guo Y; Li X
    Med Phys; 2019 Aug; 46(8):3532-3542. PubMed ID: 31087327
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Construction and application of a lung cancer stem cell model: antitumor drug screening and molecular mechanism of the inhibitory effects of sanguinarine.
    Yang J; Fang Z; Wu J; Yin X; Fang Y; Zhao F; Zhu S; Li Y
    Tumour Biol; 2016 Oct; 37(10):13871-13883. PubMed ID: 27485114
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.