These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

152 related articles for article (PubMed ID: 32323089)

  • 1. SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation.
    Yang T; Wu T; Li L; Zhu C
    J Digit Imaging; 2020 Aug; 33(4):946-957. PubMed ID: 32323089
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SRV-GAN: A generative adversarial network for segmenting retinal vessels.
    Yue C; Ye M; Wang P; Huang D; Lu X
    Math Biosci Eng; 2022 Jul; 19(10):9948-9965. PubMed ID: 36031977
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Densely connected U-Net retinal vessel segmentation algorithm based on multi-scale feature convolution extraction.
    Du X; Wang J; Sun W
    Med Phys; 2021 Jul; 48(7):3827-3841. PubMed ID: 34028030
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Generative Adversarial Network Combined with SE-ResNet and Dilated Inception Block for Segmenting Retinal Vessels.
    Yue C; Ye M; Wang P; Huang D; Lu X
    Comput Intell Neurosci; 2022; 2022():3585506. PubMed ID: 36072751
    [TBL] [Abstract][Full Text] [Related]  

  • 5. AA-WGAN: Attention augmented Wasserstein generative adversarial network with application to fundus retinal vessel segmentation.
    Liu M; Wang Z; Li H; Wu P; Alsaadi FE; Zeng N
    Comput Biol Med; 2023 May; 158():106874. PubMed ID: 37019013
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Multi-Level Attention Network for Retinal Vessel Segmentation.
    Yuan Y; Zhang L; Wang L; Huang H
    IEEE J Biomed Health Inform; 2022 Jan; 26(1):312-323. PubMed ID: 34129508
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A novel retinal vessel detection approach based on multiple deep convolution neural networks.
    Guo Y; Budak Ü; Şengür A
    Comput Methods Programs Biomed; 2018 Dec; 167():43-48. PubMed ID: 30501859
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Segmentation of retinal vessels by fusing contour information and conditional generative adversarial].
    Liang L; Lan Z; Sheng X; Xie Z; Liu W
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2021 Apr; 38(2):276-285. PubMed ID: 33913287
    [TBL] [Abstract][Full Text] [Related]  

  • 9. TDCAU-Net: retinal vessel segmentation using transformer dilated convolutional attention-based U-Net method.
    Li C; Li Z; Liu W
    Phys Med Biol; 2023 Dec; 69(1):. PubMed ID: 38052089
    [TBL] [Abstract][Full Text] [Related]  

  • 10. DAVS-NET: Dense Aggregation Vessel Segmentation Network for retinal vasculature detection in fundus images.
    Raza M; Naveed K; Akram A; Salem N; Afaq A; Madni HA; Khan MAU; Din MZ
    PLoS One; 2021; 16(12):e0261698. PubMed ID: 34972109
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Fast and efficient retinal blood vessel segmentation method based on deep learning network.
    Boudegga H; Elloumi Y; Akil M; Hedi Bedoui M; Kachouri R; Abdallah AB
    Comput Med Imaging Graph; 2021 Jun; 90():101902. PubMed ID: 33892389
    [TBL] [Abstract][Full Text] [Related]  

  • 12. SegR-Net: A deep learning framework with multi-scale feature fusion for robust retinal vessel segmentation.
    Ryu J; Rehman MU; Nizami IF; Chong KT
    Comput Biol Med; 2023 Sep; 163():107132. PubMed ID: 37343468
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A new robust method for blood vessel segmentation in retinal fundus images based on weighted line detector and hidden Markov model.
    Zhou C; Zhang X; Chen H
    Comput Methods Programs Biomed; 2020 Apr; 187():105231. PubMed ID: 31786454
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Segmentation of retinal vessels in fundus images based on U-Net with self-calibrated convolutions and spatial attention modules.
    Rong Y; Xiong Y; Li C; Chen Y; Wei P; Wei C; Fan Z
    Med Biol Eng Comput; 2023 Jul; 61(7):1745-1755. PubMed ID: 36899285
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Segmenting retinal vessels with revised top-bottom-hat transformation and flattening of minimum circumscribed ellipse.
    Wang W; Wang W; Hu Z
    Med Biol Eng Comput; 2019 Jul; 57(7):1481-1496. PubMed ID: 30903529
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Perception-oriented generative adversarial network for retinal fundus image super-resolution.
    Zhao L; Chi H; Zhong T; Jia Y
    Comput Biol Med; 2024 Jan; 168():107708. PubMed ID: 37995535
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Partial class activation mapping guided graph convolution cascaded U-Net for retinal vessel segmentation.
    Wang Z; Jia LV; Liang H
    Comput Biol Med; 2024 Aug; 178():108736. PubMed ID: 38878402
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A retinal vessel segmentation network with multiple-dimension attention and adaptive feature fusion.
    Li J; Gao G; Yang L; Liu Y
    Comput Biol Med; 2024 Apr; 172():108315. PubMed ID: 38503093
    [TBL] [Abstract][Full Text] [Related]  

  • 19. BSEResU-Net: An attention-based before-activation residual U-Net for retinal vessel segmentation.
    Li D; Rahardja S
    Comput Methods Programs Biomed; 2021 Jun; 205():106070. PubMed ID: 33857703
    [TBL] [Abstract][Full Text] [Related]  

  • 20. BSCN: bidirectional symmetric cascade network for retinal vessel segmentation.
    Guo Y; Peng Y
    BMC Med Imaging; 2020 Feb; 20(1):20. PubMed ID: 32070306
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.