BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

314 related articles for article (PubMed ID: 36635120)

  • 1. Eres-UNet++: Liver CT image segmentation based on high-efficiency channel attention and Res-UNet+.
    Li J; Liu K; Hu Y; Zhang H; Heidari AA; Chen H; Zhang W; Algarni AD; Elmannai H
    Comput Biol Med; 2023 May; 158():106501. PubMed ID: 36635120
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Multi-scale attention and deep supervision-based 3D UNet for automatic liver segmentation from CT.
    Wang J; Zhang X; Guo L; Shi C; Tamura S
    Math Biosci Eng; 2023 Jan; 20(1):1297-1316. PubMed ID: 36650812
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Improved UNet with Attention for Medical Image Segmentation.
    Al Qurri A; Almekkawy M
    Sensors (Basel); 2023 Oct; 23(20):. PubMed ID: 37896682
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Residual based attention-Unet combing DAC and RMP modules for automatic liver tumor segmentation in CT.
    Bi R; Ji C; Yang Z; Qiao M; Lv P; Wang H
    Math Biosci Eng; 2022 Mar; 19(5):4703-4718. PubMed ID: 35430836
    [No Abstract]   [Full Text] [Related]  

  • 6. SADSNet: A robust 3D synchronous segmentation network for liver and liver tumors based on spatial attention mechanism and deep supervision.
    Yang S; Liang Y; Wu S; Sun P; Chen Z
    J Xray Sci Technol; 2024; 32(3):707-723. PubMed ID: 38552134
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Multi-scale context UNet-like network with redesigned skip connections for medical image segmentation.
    Qian L; Wen C; Li Y; Hu Z; Zhou X; Xia X; Kim SH
    Comput Methods Programs Biomed; 2024 Jan; 243():107885. PubMed ID: 37897988
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Medical lesion segmentation by combining multimodal images with modality weighted UNet.
    Zhu X; Wu Y; Hu H; Zhuang X; Yao J; Ou D; Li W; Song M; Feng N; Xu D
    Med Phys; 2022 Jun; 49(6):3692-3704. PubMed ID: 35312077
    [TBL] [Abstract][Full Text] [Related]  

  • 10. UNet segmentation network of COVID-19 CT images with multi-scale attention.
    Chen M; Yi S; Yang M; Yang Z; Zhang X
    Math Biosci Eng; 2023 Aug; 20(9):16762-16785. PubMed ID: 37920033
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Brain tumor magnetic resonance image segmentation by a multiscale contextual attention module combined with a deep residual UNet (MCA-ResUNet).
    Cao T; Wang G; Ren L; Li Y; Wang H
    Phys Med Biol; 2022 Apr; 67(9):. PubMed ID: 35294935
    [No Abstract]   [Full Text] [Related]  

  • 12. BPAT-UNet: Boundary preserving assembled transformer UNet for ultrasound thyroid nodule segmentation.
    Bi H; Cai C; Sun J; Jiang Y; Lu G; Shu H; Ni X
    Comput Methods Programs Biomed; 2023 Aug; 238():107614. PubMed ID: 37244233
    [TBL] [Abstract][Full Text] [Related]  

  • 13. CARes-UNet: Content-aware residual UNet for lesion segmentation of COVID-19 from chest CT images.
    Xu X; Wen Y; Zhao L; Zhang Y; Zhao Y; Tang Z; Yang Z; Chen CY
    Med Phys; 2021 Nov; 48(11):7127-7140. PubMed ID: 34528263
    [TBL] [Abstract][Full Text] [Related]  

  • 14. PA-ResSeg: A phase attention residual network for liver tumor segmentation from multiphase CT images.
    Xu Y; Cai M; Lin L; Zhang Y; Hu H; Peng Z; Zhang Q; Chen Q; Mao X; Iwamoto Y; Han XH; Chen YW; Tong R
    Med Phys; 2021 Jul; 48(7):3752-3766. PubMed ID: 33950526
    [TBL] [Abstract][Full Text] [Related]  

  • 15. ECA-TFUnet: A U-shaped CNN-Transformer network with efficient channel attention for organ segmentation in anatomical sectional images of canines.
    Liu Y; Liu Y; Li J; Chen Y; Xu F; Xu Y; Cao J; Ma Y
    Math Biosci Eng; 2023 Oct; 20(10):18650-18669. PubMed ID: 38052573
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A deep residual attention-based U-Net with a biplane joint method for liver segmentation from CT scans.
    Chen Y; Zheng C; Zhou T; Feng L; Liu L; Zeng Q; Wang G
    Comput Biol Med; 2023 Jan; 152():106421. PubMed ID: 36527780
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Dual attention fusion UNet for COVID-19 lesion segmentation from CT images.
    Ma Y; Zhang Y; Chen L; Jiang Q; Wei B
    J Xray Sci Technol; 2023; 31(4):713-729. PubMed ID: 37092210
    [TBL] [Abstract][Full Text] [Related]  

  • 18. C
    Luo S; Jiang H; Wang M
    Comput Med Imaging Graph; 2023 Jan; 103():102159. PubMed ID: 36549193
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Channel-Unet: A Spatial Channel-Wise Convolutional Neural Network for Liver and Tumors Segmentation.
    Chen Y; Wang K; Liao X; Qian Y; Wang Q; Yuan Z; Heng PA
    Front Genet; 2019; 10():1110. PubMed ID: 31827487
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field.
    Chen Y; Zheng C; Hu F; Zhou T; Feng L; Xu G; Yi Z; Zhang X
    Comput Biol Med; 2022 Nov; 150():106076. PubMed ID: 36137320
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.