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 *

302 related articles for article (PubMed ID: 35015305)

  • 41. 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]  

  • 42. ELTS-Net: An enhanced liver tumor segmentation network with augmented receptive field and global contextual information.
    Guo X; Wang Z; Wu P; Li Y; Alsaadi FE; Zeng N
    Comput Biol Med; 2024 Feb; 169():107879. PubMed ID: 38142549
    [TBL] [Abstract][Full Text] [Related]  

  • 43. ABCNet: A new efficient 3D dense-structure network for segmentation and analysis of body tissue composition on body-torso-wide CT images.
    Liu T; Pan J; Torigian DA; Xu P; Miao Q; Tong Y; Udupa JK
    Med Phys; 2020 Jul; 47(7):2986-2999. PubMed ID: 32170754
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Residual Deformable Split Channel and Spatial U-Net for Automated Liver and Liver Tumour Segmentation.
    Saumiya S; Franklin SW
    J Digit Imaging; 2023 Oct; 36(5):2164-2178. PubMed ID: 37464213
    [TBL] [Abstract][Full Text] [Related]  

  • 45. HFCF-Net: A hybrid-feature cross fusion network for COVID-19 lesion segmentation from CT volumetric images.
    Wang Y; Yang Q; Tian L; Zhou X; Rekik I; Huang H
    Med Phys; 2022 Jun; 49(6):3797-3815. PubMed ID: 35301729
    [TBL] [Abstract][Full Text] [Related]  

  • 46. S2DA-Net: Spatial and spectral-learning double-branch aggregation network for liver tumor segmentation in CT images.
    Liu H; Yang J; Jiang C; He S; Fu Y; Zhang S; Hu X; Fang J; Ji W
    Comput Biol Med; 2024 May; 174():108400. PubMed ID: 38613888
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Vessel segmentation from volumetric images: a multi-scale double-pathway network with class-balanced loss at the voxel level.
    Chen Y; Fan S; Chen Y; Che C; Cao X; He X; Song X; Zhao F
    Med Phys; 2021 Jul; 48(7):3804-3814. PubMed ID: 33969487
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Liver tumor segmentation in CT volumes using an adversarial densely connected network.
    Chen L; Song H; Wang C; Cui Y; Yang J; Hu X; Zhang L
    BMC Bioinformatics; 2019 Dec; 20(Suppl 16):587. PubMed ID: 31787071
    [TBL] [Abstract][Full Text] [Related]  

  • 49. CFHA-Net: A polyp segmentation method with cross-scale fusion strategy and hybrid attention.
    Yang L; Zhai C; Liu Y; Yu H
    Comput Biol Med; 2023 Sep; 164():107301. PubMed ID: 37573723
    [TBL] [Abstract][Full Text] [Related]  

  • 50. 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]  

  • 51. Self-channel-and-spatial-attention neural network for automated multi-organ segmentation on head and neck CT images.
    Gou S; Tong N; Qi S; Yang S; Chin R; Sheng K
    Phys Med Biol; 2020 Dec; 65(24):245034. PubMed ID: 32097892
    [TBL] [Abstract][Full Text] [Related]  

  • 52. 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]  

  • 53. Liver vessel segmentation based on inter-scale V-Net.
    Yang J; Fu M; Hu Y
    Math Biosci Eng; 2021 May; 18(4):4327-4340. PubMed ID: 34198439
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Performance improvement of weakly supervised fully convolutional networks by skip connections for brain structure segmentation.
    Sugino T; Roth HR; Oda M; Kin T; Saito N; Nakajima Y; Mori K
    Med Phys; 2021 Nov; 48(11):7215-7227. PubMed ID: 34453333
    [TBL] [Abstract][Full Text] [Related]  

  • 55. 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]  

  • 56. 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]  

  • 57. A Multi-Scale Context Aware Attention Model for Medical Image Segmentation.
    Alam MS; Wang D; Liao Q; Sowmya A
    IEEE J Biomed Health Inform; 2023 Aug; 27(8):3731-3739. PubMed ID: 37015493
    [TBL] [Abstract][Full Text] [Related]  

  • 58. A Dynamic Context Encoder Network for Liver Tumor Segmentation.
    Liu J; Fang J; Jiang T; Zhou C; Shao L; Song Y
    Curr Med Imaging; 2024; 20():e15734056303257. PubMed ID: 38874025
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Context fusion network with multi-scale-aware skip connection and twin-split attention for liver tumor segmentation.
    Wang Z; Zhu J; Fu S; Ye Y
    Med Biol Eng Comput; 2023 Dec; 61(12):3167-3180. PubMed ID: 37470963
    [TBL] [Abstract][Full Text] [Related]  

  • 60. TransU²-Net: An Effective Medical Image Segmentation Framework Based on Transformer and U²-Net.
    Li X; Fang X; Yang G; Su S; Zhu L; Yu Z
    IEEE J Transl Eng Health Med; 2023; 11():441-450. PubMed ID: 37817826
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 16.