BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

166 related articles for article (PubMed ID: 34921356)

  • 1. Multi-scale Selection and Multi-channel Fusion Model for Pancreas Segmentation Using Adversarial Deep Convolutional Nets.
    Li M; Lian F; Guo S
    J Digit Imaging; 2022 Feb; 35(1):47-55. PubMed ID: 34921356
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Accurate pancreas segmentation using multi-level pyramidal pooling residual U-Net with adversarial mechanism.
    Li M; Lian F; Wang C; Guo S
    BMC Med Imaging; 2021 Nov; 21(1):168. PubMed ID: 34772359
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep multi-scale feature fusion for pancreas segmentation from CT images.
    Chen Z; Wang X; Yan K; Zheng J
    Int J Comput Assist Radiol Surg; 2020 Mar; 15(3):415-423. PubMed ID: 31970601
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.
    Roth HR; Lu L; Lay N; Harrison AP; Farag A; Sohn A; Summers RM
    Med Image Anal; 2018 Apr; 45():94-107. PubMed ID: 29427897
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multi-scale U-like network with attention mechanism for automatic pancreas segmentation.
    Yan Y; Zhang D
    PLoS One; 2021; 16(5):e0252287. PubMed ID: 34043732
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Attention-guided duplex adversarial U-net for pancreatic segmentation from computed tomography images.
    Li M; Lian F; Li Y; Guo S
    J Appl Clin Med Phys; 2022 Apr; 23(4):e13537. PubMed ID: 35199477
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Pancreas segmentation based on an adversarial model under two-tier constraints.
    Li M; Lian F; Guo S
    Phys Med Biol; 2020 Nov; 65(22):225021. PubMed ID: 32906095
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Dual adversarial convolutional networks with multilevel cues for pancreatic segmentation.
    Li M; Lian F; Wang C; Guo S
    Phys Med Biol; 2021 Aug; 66(17):. PubMed ID: 34271564
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.
    Fu M; Wu W; Hong X; Liu Q; Jiang J; Ou Y; Zhao Y; Gong X
    BMC Syst Biol; 2018 Apr; 12(Suppl 4):56. PubMed ID: 29745840
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multiscale unsupervised domain adaptation for automatic pancreas segmentation in CT volumes using adversarial learning.
    Zhu Y; Hu P; Li X; Tian Y; Bai X; Liang T; Li J
    Med Phys; 2022 Sep; 49(9):5799-5818. PubMed ID: 35833617
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Robust and efficient abdominal CT segmentation using shape constrained multi-scale attention network.
    Tong N; Xu Y; Zhang J; Gou S; Li M
    Phys Med; 2023 Jun; 110():102595. PubMed ID: 37178624
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pancreas Segmentation in Abdominal CT Scans using Inter-/Intra-Slice Contextual Information with a Cascade Neural Network.
    Yang Z; Zhang L; Zhang M; Feng J; Wu Z; Ren F; Lv Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():5937-5940. PubMed ID: 31947200
    [TBL] [Abstract][Full Text] [Related]  

  • 13. [Lung parenchyma segmentation based on double scale parallel attention network].
    Feng K; Ren L; Wu Y; Li Y; Wang H; Wang G
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2022 Aug; 39(4):721-729. PubMed ID: 36008336
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic Pancreas Segmentation in CT Images With Distance-Based Saliency-Aware DenseASPP Network.
    Hu P; Li X; Tian Y; Tang T; Zhou T; Bai X; Zhu S; Liang T; Li J
    IEEE J Biomed Health Inform; 2021 May; 25(5):1601-1611. PubMed ID: 32915752
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Abdominal multi-organ segmentation with organ-attention networks and statistical fusion.
    Wang Y; Zhou Y; Shen W; Park S; Fishman EK; Yuille AL
    Med Image Anal; 2019 Jul; 55():88-102. PubMed ID: 31035060
    [TBL] [Abstract][Full Text] [Related]  

  • 16. HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images.
    Yuan N; Zhang Y; Lv K; Liu Y; Yang A; Hu P; Yu H; Han X; Guo X; Li J; Wang T; Lei B; Ma G
    Cancer Imaging; 2024 May; 24(1):63. PubMed ID: 38773670
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Cross-convolutional transformer for automated multi-organs segmentation in a variety of medical images.
    Wang J; Zhao H; Liang W; Wang S; Zhang Y
    Phys Med Biol; 2023 Jan; 68(3):. PubMed ID: 36623323
    [No Abstract]   [Full Text] [Related]  

  • 18. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.
    Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH
    Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Cascaded atrous convolution and spatial pyramid pooling for more accurate tumor target segmentation for rectal cancer radiotherapy.
    Men K; Boimel P; Janopaul-Naylor J; Zhong H; Huang M; Geng H; Cheng C; Fan Y; Plastaras JP; Ben-Josef E; Xiao Y
    Phys Med Biol; 2018 Sep; 63(18):185016. PubMed ID: 30109986
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
    Tong N; Gou S; Yang S; Ruan D; Sheng K
    Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.