BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 38470598)

  • 1. SCAC: A Semi-Supervised Learning Approach for Cervical Abnormal Cell Detection.
    Zhang Z; Yao P; Chen M; Zeng L; Shao P; Shen S; Xu RX
    IEEE J Biomed Health Inform; 2024 Jun; 28(6):3501-3512. PubMed ID: 38470598
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PolypMixNet: Enhancing semi-supervised polyp segmentation with polyp-aware augmentation.
    Jia X; Shen Y; Yang J; Song R; Zhang W; Meng MQ; Liao JC; Xing L
    Comput Biol Med; 2024 Mar; 170():108006. PubMed ID: 38325216
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-guided Semi-supervised Medical Image Segmentation.
    Xiao Z; Su Y; Deng Z; Zhang W
    Comput Methods Programs Biomed; 2022 Nov; 226():107099. PubMed ID: 36116398
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CervixFormer: A Multi-scale swin transformer-Based cervical pap-Smear WSI classification framework.
    Khan A; Han S; Ilyas N; Lee YM; Lee B
    Comput Methods Programs Biomed; 2023 Oct; 240():107718. PubMed ID: 37451230
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A modality-collaborative convolution and transformer hybrid network for unpaired multi-modal medical image segmentation with limited annotations.
    Liu H; Zhuang Y; Song E; Xu X; Ma G; Cetinkaya C; Hung CC
    Med Phys; 2023 Sep; 50(9):5460-5478. PubMed ID: 36864700
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation.
    Chaitanya K; Erdil E; Karani N; Konukoglu E
    Med Image Anal; 2023 Jul; 87():102792. PubMed ID: 37054649
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Semi-TMS: an efficient regularization-oriented triple-teacher semi-supervised medical image segmentation model.
    Chen W; Zhou S; Liu X; Chen Y
    Phys Med Biol; 2023 Oct; 68(20):. PubMed ID: 37699409
    [No Abstract]   [Full Text] [Related]  

  • 8. A novel attention-guided convolutional network for the detection of abnormal cervical cells in cervical cancer screening.
    Cao L; Yang J; Rong Z; Li L; Xia B; You C; Lou G; Jiang L; Du C; Meng H; Wang W; Wang M; Li K; Hou Y
    Med Image Anal; 2021 Oct; 73():102197. PubMed ID: 34403932
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.
    P B S; Faruqi F; K S H; Kudva R
    Asian Pac J Cancer Prev; 2019 Nov; 20(11):3447-3456. PubMed ID: 31759371
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Voxel-wise adversarial semi-supervised learning for medical image segmentation.
    Lee CE; Park H; Shin YG; Chung M
    Comput Biol Med; 2022 Nov; 150():106152. PubMed ID: 36208595
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency.
    Luo X; Wang G; Liao W; Chen J; Song T; Chen Y; Zhang S; Metaxas DN; Zhang S
    Med Image Anal; 2022 Aug; 80():102517. PubMed ID: 35732106
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.
    Kurita Y; Meguro S; Tsuyama N; Kosugi I; Enomoto Y; Kawasaki H; Uemura T; Kimura M; Iwashita T
    PLoS One; 2023; 18(5):e0285996. PubMed ID: 37200281
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Attention decoupled contrastive learning for semi-supervised segmentation method based on data augmentation.
    Pan P; Chen H; Li Y; Peng W; Cheng L
    Phys Med Biol; 2024 Jun; 69(12):. PubMed ID: 38759677
    [No Abstract]   [Full Text] [Related]  

  • 14. Uncertainty-guided cross learning via CNN and transformer for semi-supervised honeycomb lung lesion segmentation.
    Zi-An Z; Xiu-Fang F; Xiao-Qiang R; Yun-Yun D
    Phys Med Biol; 2023 Dec; 68(24):. PubMed ID: 37988756
    [No Abstract]   [Full Text] [Related]  

  • 15. Deep virtual adversarial self-training with consistency regularization for semi-supervised medical image classification.
    Wang X; Chen H; Xiang H; Lin H; Lin X; Heng PA
    Med Image Anal; 2021 May; 70():102010. PubMed ID: 33677262
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images.
    Yuan C; Yao Y; Cheng B; Cheng Y; Li Y; Li Y; Liu X; Cheng X; Xie X; Wu J; Wang X; Lu W
    Sci Rep; 2020 Jul; 10(1):11639. PubMed ID: 32669565
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis.
    Wang X; Chen H; Gan C; Lin H; Dou Q; Tsougenis E; Huang Q; Cai M; Heng PA
    IEEE Trans Cybern; 2020 Sep; 50(9):3950-3962. PubMed ID: 31484154
    [TBL] [Abstract][Full Text] [Related]  

  • 18. An efficient Fusion-Purification Network for Cervical pap-smear image classification.
    Yang T; Hu H; Li X; Meng Q; Lu H; Huang Q
    Comput Methods Programs Biomed; 2024 Jun; 251():108199. PubMed ID: 38728830
    [TBL] [Abstract][Full Text] [Related]  

  • 19. BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning.
    Sheng H; Ma L; Samson JF; Liu D
    BMC Med Inform Decis Mak; 2024 May; 24(1):126. PubMed ID: 38755563
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images.
    Gao F; Hu M; Zhong ME; Feng S; Tian X; Meng X; Ni-Jia-Ti MY; Huang Z; Lv M; Song T; Zhang X; Zou X; Wu X
    Med Image Anal; 2022 Aug; 80():102515. PubMed ID: 35780593
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.