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 *

145 related articles for article (PubMed ID: 34305162)

  • 1. RCTE: A reliable and consistent temporal-ensembling framework for semi-supervised segmentation of COVID-19 lesions.
    Ding W; Abdel-Basset M; Hawash H
    Inf Sci (N Y); 2021 Nov; 578():559-573. PubMed ID: 34305162
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images.
    Wang G; Liu X; Li C; Xu Z; Ruan J; Zhu H; Meng T; Li K; Huang N; Zhang S
    IEEE Trans Med Imaging; 2020 Aug; 39(8):2653-2663. PubMed ID: 32730215
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images.
    Liu X; Yuan Q; Gao Y; He K; Wang S; Tang X; Tang J; Shen D
    Pattern Recognit; 2022 Feb; 122():108341. PubMed ID: 34565913
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT.
    Hussain MA; Mirikharaji Z; Momeny M; Marhamati M; Neshat AA; Garbi R; Hamarneh G
    Comput Med Imaging Graph; 2022 Dec; 102():102127. PubMed ID: 36257092
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Constantly optimized mean teacher for semi-supervised 3D MRI image segmentation.
    Li N; Pan Y; Qiu W; Xiong L; Wang Y; Zhang Y
    Med Biol Eng Comput; 2024 Jul; 62(7):2231-2245. PubMed ID: 38514501
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. SSA-Net: Spatial self-attention network for COVID-19 pneumonia infection segmentation with semi-supervised few-shot learning.
    Wang X; Yuan Y; Guo D; Huang X; Cui Y; Xia M; Wang Z; Bai C; Chen S
    Med Image Anal; 2022 Jul; 79():102459. PubMed ID: 35544999
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MTAN: A semi-supervised learning model for kidney tumor segmentation.
    Sun P; Yang S; Guan H; Mo T; Yu B; Chen Z
    J Xray Sci Technol; 2023; 31(6):1295-1313. PubMed ID: 37718833
    [TBL] [Abstract][Full Text] [Related]  

  • 9. MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation.
    Chen G; Ru J; Zhou Y; Rekik I; Pan Z; Liu X; Lin Y; Lu B; Shi J
    Neuroimage; 2021 Dec; 244():118568. PubMed ID: 34508895
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning.
    Wang K; Zhan B; Zu C; Wu X; Zhou J; Zhou L; Wang Y
    Med Image Anal; 2022 Jul; 79():102447. PubMed ID: 35509136
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Uncertainty Aware Temporal-Ensembling Model for Semi-Supervised ABUS Mass Segmentation.
    Cao X; Chen H; Li Y; Peng Y; Wang S; Cheng L
    IEEE Trans Med Imaging; 2021 Jan; 40(1):431-443. PubMed ID: 33021936
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Semi-supervised image segmentation using a residual-driven mean teacher and an exponential Dice loss.
    Mei C; Yang X; Zhou M; Zhang S; Chen H; Yang X; Wang L
    Artif Intell Med; 2024 Feb; 148():102757. PubMed ID: 38325920
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Self-Ensembling Co-Training Framework for Semi-Supervised COVID-19 CT Segmentation.
    Li C; Dong L; Dou Q; Lin F; Zhang K; Feng Z; Si W; Deng X; Deng Z; Heng PA
    IEEE J Biomed Health Inform; 2021 Nov; 25(11):4140-4151. PubMed ID: 34375293
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Learning COVID-19 Pneumonia Lesion Segmentation From Imperfect Annotations via Divergence-Aware Selective Training.
    Yang S; Wang G; Sun H; Luo X; Sun P; Li K; Wang Q; Zhang S
    IEEE J Biomed Health Inform; 2022 Aug; 26(8):3673-3684. PubMed ID: 35522641
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Semi-supervised OCT lesion segmentation via transformation-consistent with uncertainty and self-deep supervision.
    Shen H; Yang Q; Chen Z; Ye Z; Dai P; Duan X
    Biomed Opt Express; 2023 Jul; 14(7):3828-3840. PubMed ID: 37497513
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Weakly-Supervised teacher-Student network for liver tumor segmentation from non-enhanced images.
    Zhang D; Chen B; Chong J; Li S
    Med Image Anal; 2021 May; 70():102005. PubMed ID: 33676099
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. FSS-2019-nCov: A deep learning architecture for semi-supervised few-shot segmentation of COVID-19 infection.
    Abdel-Basset M; Chang V; Hawash H; Chakrabortty RK; Ryan M
    Knowl Based Syst; 2021 Jan; 212():106647. PubMed ID: 33519100
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Semi-Supervised Segmentation of Interstitial Lung Disease Patterns from CT Images via Self-Training with Selective Re-Training.
    Cai GW; Liu YB; Feng QJ; Liang RH; Zeng QS; Deng Y; Yang W
    Bioengineering (Basel); 2023 Jul; 10(7):. PubMed ID: 37508857
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A teacher-student framework with Fourier Transform augmentation for COVID-19 infection segmentation in CT images.
    Chen H; Jiang Y; Ko H; Loew M
    Biomed Signal Process Control; 2023 Jan; 79():104250. PubMed ID: 36188130
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.