BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

419 related articles for article (PubMed ID: 36609788)

  • 1. TrEnD: A transformer-based encoder-decoder model with adaptive patch embedding for mass segmentation in mammograms.
    Liu D; Wu B; Li C; Sun Z; Zhang N
    Med Phys; 2023 May; 50(5):2884-2899. PubMed ID: 36609788
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. DCANet: Dual contextual affinity network for mass segmentation in whole mammograms.
    Lou M; Qi Y; Meng J; Xu C; Wang Y; Pi J; Ma Y
    Med Phys; 2021 Aug; 48(8):4291-4303. PubMed ID: 34061371
    [TBL] [Abstract][Full Text] [Related]  

  • 4. FS-UNet: Mass segmentation in mammograms using an encoder-decoder architecture with feature strengthening.
    Pi J; Qi Y; Lou M; Li X; Wang Y; Xu C; Ma Y
    Comput Biol Med; 2021 Oct; 137():104800. PubMed ID: 34507155
    [TBL] [Abstract][Full Text] [Related]  

  • 5. AUNet: attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms.
    Sun H; Li C; Liu B; Liu Z; Wang M; Zheng H; Dagan Feng D; Wang S
    Phys Med Biol; 2020 Feb; 65(5):055005. PubMed ID: 31722327
    [TBL] [Abstract][Full Text] [Related]  

  • 6. YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms.
    Su Y; Liu Q; Xie W; Hu P
    Comput Methods Programs Biomed; 2022 Jun; 221():106903. PubMed ID: 35636358
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Connected-UNets: a deep learning architecture for breast mass segmentation.
    Baccouche A; Garcia-Zapirain B; Castillo Olea C; Elmaghraby AS
    NPJ Breast Cancer; 2021 Dec; 7(1):151. PubMed ID: 34857755
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Convolutional neural network for automated mass segmentation in mammography.
    Abdelhafiz D; Bi J; Ammar R; Yang C; Nabavi S
    BMC Bioinformatics; 2020 Dec; 21(Suppl 1):192. PubMed ID: 33297952
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Mass segmentation for whole mammograms via attentive multi-task learning framework.
    Hou X; Bai Y; Xie Y; Li Y
    Phys Med Biol; 2021 May; 66(10):. PubMed ID: 33882475
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MESTrans: Multi-scale embedding spatial transformer for medical image segmentation.
    Liu Y; Zhu Y; Xin Y; Zhang Y; Yang D; Xu T
    Comput Methods Programs Biomed; 2023 May; 233():107493. PubMed ID: 36965298
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Whole mammographic mass segmentation using attention mechanism and multiscale pooling adversarial network.
    Wang Y; Wang S; Chen J; Wu C
    J Med Imaging (Bellingham); 2020 Sep; 7(5):054503. PubMed ID: 33102621
    [No Abstract]   [Full Text] [Related]  

  • 12. Multi-Level Swin Transformer Enabled Automatic Segmentation and Classification of Breast Metastases.
    Masood A; Naseem U; Kim J
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38082574
    [TBL] [Abstract][Full Text] [Related]  

  • 13. TSCA-Net: Transformer based spatial-channel attention segmentation network for medical images.
    Fu Y; Liu J; Shi J
    Comput Biol Med; 2024 Mar; 170():107938. PubMed ID: 38219644
    [TBL] [Abstract][Full Text] [Related]  

  • 14. TPFR-Net: U-shaped model for lung nodule segmentation based on transformer pooling and dual-attention feature reorganization.
    Li X; Jiang A; Qiu Y; Li M; Zhang X; Yan S
    Med Biol Eng Comput; 2023 Aug; 61(8):1929-1946. PubMed ID: 37243853
    [TBL] [Abstract][Full Text] [Related]  

  • 15. HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.
    He Q; Yang Q; Xie M
    Comput Biol Med; 2023 Mar; 155():106629. PubMed ID: 36787669
    [TBL] [Abstract][Full Text] [Related]  

  • 16. HMA-Net: A deep U-shaped network combined with HarDNet and multi-attention mechanism for medical image segmentation.
    Liu Q; Han Z; Liu Z; Zhang J
    Med Phys; 2023 Mar; 50(3):1635-1646. PubMed ID: 36303466
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Breast ultrasound image segmentation: A coarse-to-fine fusion convolutional neural network.
    Wang K; Liang S; Zhong S; Feng Q; Ning Z; Zhang Y
    Med Phys; 2021 Aug; 48(8):4262-4278. PubMed ID: 34053092
    [TBL] [Abstract][Full Text] [Related]  

  • 18. ETUNet:Exploring efficient transformer enhanced UNet for 3D brain tumor segmentation.
    Zhang W; Chen S; Ma Y; Liu Y; Cao X
    Comput Biol Med; 2024 Mar; 171():108005. PubMed ID: 38340437
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mammogram mass segmentation and classification based on cross-view VAE and spatial hidden factor disentanglement.
    Ma Y; Peng Y
    Phys Eng Sci Med; 2024 Mar; 47(1):223-238. PubMed ID: 38150059
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Transformer guided self-adaptive network for multi-scale skin lesion image segmentation.
    Xin C; Liu Z; Ma Y; Wang D; Zhang J; Li L; Zhou Q; Xu S; Zhang Y
    Comput Biol Med; 2024 Feb; 169():107846. PubMed ID: 38184865
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 21.