BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

246 related articles for article (PubMed ID: 38326677)

  • 1. ASD-Net: a novel U-Net based asymmetric spatial-channel convolution network for precise kidney and kidney tumor image segmentation.
    Ji Z; Mu J; Liu J; Zhang H; Dai C; Zhang X; Ganchev I
    Med Biol Eng Comput; 2024 Jun; 62(6):1673-1687. PubMed ID: 38326677
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A multiple-channel and atrous convolution network for ultrasound image segmentation.
    Zhang L; Zhang J; Li Z; Song Y
    Med Phys; 2020 Dec; 47(12):6270-6285. PubMed ID: 33007105
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images.
    Balraj K; Ramteke M; Mittal S; Bhargava R; Rathore AS
    Sci Rep; 2024 Jun; 14(1):12699. PubMed ID: 38830932
    [TBL] [Abstract][Full Text] [Related]  

  • 4. SAR-U-Net: Squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography.
    Wang J; Lv P; Wang H; Shi C
    Comput Methods Programs Biomed; 2021 Sep; 208():106268. PubMed ID: 34274611
    [TBL] [Abstract][Full Text] [Related]  

  • 5. ASU-Net++: A nested U-Net with adaptive feature extractions for liver tumor segmentation.
    Gao Q; Almekkawy M
    Comput Biol Med; 2021 Sep; 136():104688. PubMed ID: 34523421
    [TBL] [Abstract][Full Text] [Related]  

  • 6. HFRU-Net: High-Level Feature Fusion and Recalibration UNet for Automatic Liver and Tumor Segmentation in CT Images.
    Kushnure DT; Talbar SN
    Comput Methods Programs Biomed; 2022 Jan; 213():106501. PubMed ID: 34752959
    [TBL] [Abstract][Full Text] [Related]  

  • 7. SK-Unet++: An improved Unet++ network with adaptive receptive fields for automatic segmentation of ultrasound thyroid nodule images.
    Dai H; Xie W; Xia E
    Med Phys; 2024 Mar; 51(3):1798-1811. PubMed ID: 37606374
    [TBL] [Abstract][Full Text] [Related]  

  • 8. GC-Net: Global context network for medical image segmentation.
    Ni J; Wu J; Tong J; Chen Z; Zhao J
    Comput Methods Programs Biomed; 2020 Jul; 190():105121. PubMed ID: 31623863
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Modified U-Net (mU-Net) With Incorporation of Object-Dependent High Level Features for Improved Liver and Liver-Tumor Segmentation in CT Images.
    Seo H; Huang C; Bassenne M; Xiao R; Xing L
    IEEE Trans Med Imaging; 2020 May; 39(5):1316-1325. PubMed ID: 31634827
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MHSU-Net: A more versatile neural network for medical image segmentation.
    Ma H; Zou Y; Liu PX
    Comput Methods Programs Biomed; 2021 Sep; 208():106230. PubMed ID: 34148011
    [TBL] [Abstract][Full Text] [Related]  

  • 11. [Fully Automatic Glioma Segmentation Algorithm of Magnetic Resonance Imaging Based on 3D-UNet With More Global Contextual Feature Extraction: An Improvement on Insufficient Extraction of Global Features].
    Tian H; Wang Y; Ji Y; Rahman MM
    Sichuan Da Xue Xue Bao Yi Xue Ban; 2024 Mar; 55(2):447-454. PubMed ID: 38645864
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.
    Liu Z; Yuan H; Wang H
    Med Phys; 2022 Aug; 49(8):5294-5303. PubMed ID: 35609213
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DCU-Net: Multi-scale U-Net for brain tumor segmentation.
    Yang T; Zhou Y; Li L; Zhu C
    J Xray Sci Technol; 2020; 28(4):709-726. PubMed ID: 32444591
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Boundary Aware Semantic Segmentation using Pyramid-dilated Dense U-Net for Lung Segmentation in Computed Tomography Images.
    Agnes SA
    J Med Phys; 2023; 48(2):161-174. PubMed ID: 37576094
    [TBL] [Abstract][Full Text] [Related]  

  • 16. ADR-Net: Context extraction network based on M-Net for medical image segmentation.
    Ji L; Jiang X; Gao Y; Fang Z; Cai Q; Wei Z
    Med Phys; 2020 Sep; 47(9):4254-4264. PubMed ID: 32602963
    [TBL] [Abstract][Full Text] [Related]  

  • 17. RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images.
    Li YZ; Wang Y; Huang YH; Xiang P; Liu WX; Lai QQ; Gao YY; Xu MS; Guo YF
    Comput Methods Programs Biomed; 2023 Apr; 231():107437. PubMed ID: 36863157
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.
    Liu Y; Zhang M; Zhong Z; Zeng X
    Med Phys; 2023 Mar; 50(3):1528-1538. PubMed ID: 36057788
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Pulmonary nodule segmentation based on REMU-Net.
    Li D; Yuan S; Yao G
    Phys Eng Sci Med; 2022 Sep; 45(3):995-1004. PubMed ID: 35877020
    [TBL] [Abstract][Full Text] [Related]  

  • 20. RDCTrans U-Net: A Hybrid Variable Architecture for Liver CT Image Segmentation.
    Li L; Ma H
    Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408067
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.