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 *

175 related articles for article (PubMed ID: 34892046)

  • 1. Weakly Supervised Attention Map Training for Histological Localization of Colonoscopy Images.
    Kwon J; Choi K
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3725-3728. PubMed ID: 34892046
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Self-supervised representation learning using feature pyramid siamese networks for colorectal polyp detection.
    Gan T; Jin Z; Yu L; Liang X; Zhang H; Ye X
    Sci Rep; 2023 Dec; 13(1):21655. PubMed ID: 38066207
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images.
    Seung Yeon Shin ; Soochahn Lee ; Il Dong Yun ; Sun Mi Kim ; Kyoung Mu Lee
    IEEE Trans Med Imaging; 2019 Mar; 38(3):762-774. PubMed ID: 30273145
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated polyp segmentation for colonoscopy images: A method based on convolutional neural networks and ensemble learning.
    Guo X; Zhang N; Guo J; Zhang H; Hao Y; Hang J
    Med Phys; 2019 Dec; 46(12):5666-5676. PubMed ID: 31610020
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Weakly-supervised convolutional neural networks of renal tumor segmentation in abdominal CTA images.
    Yang G; Wang C; Yang J; Chen Y; Tang L; Shao P; Dillenseger JL; Shu H; Luo L
    BMC Med Imaging; 2020 Apr; 20(1):37. PubMed ID: 32293303
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Weakly supervised semantic segmentation of histological tissue via attention accumulation and pixel-level contrast learning.
    Han Y; Cheng L; Huang G; Zhong G; Li J; Yuan X; Liu H; Li J; Zhou J; Cai M
    Phys Med Biol; 2023 Feb; 68(4):. PubMed ID: 36577142
    [No Abstract]   [Full Text] [Related]  

  • 7. Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification.
    Marini N; Otálora S; Müller H; Atzori M
    Med Image Anal; 2021 Oct; 73():102165. PubMed ID: 34303169
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Weakly Supervised Polyp Segmentation in Colonoscopy Images Using Deep Neural Networks.
    Chen S; Urban G; Baldi P
    J Imaging; 2022 Apr; 8(5):. PubMed ID: 35621885
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An automated detection system for colonoscopy images using a dual encoder-decoder model.
    Hwang M; Wang D; Kong XX; Wang Z; Li J; Jiang WC; Hwang KS; Ding K
    Comput Med Imaging Graph; 2020 Sep; 84():101763. PubMed ID: 32805673
    [TBL] [Abstract][Full Text] [Related]  

  • 10. SR-AttNet: An Interpretable Stretch-Relax Attention based Deep Neural Network for Polyp Segmentation in Colonoscopy Images.
    Alam MJ; Fattah SA
    Comput Biol Med; 2023 Jun; 160():106945. PubMed ID: 37163966
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution.
    Safarov S; Whangbo TK
    Sensors (Basel); 2021 Feb; 21(4):. PubMed ID: 33669539
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images.
    Sebai M; Wang X; Wang T
    Med Biol Eng Comput; 2020 Jul; 58(7):1603-1623. PubMed ID: 32445109
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images.
    Zhang J; Hua Z; Yan K; Tian K; Yao J; Liu E; Liu M; Han X
    Med Image Anal; 2021 Oct; 73():102183. PubMed ID: 34340108
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network.
    Han L; Huang Y; Dou H; Wang S; Ahamad S; Luo H; Liu Q; Fan J; Zhang J
    Comput Methods Programs Biomed; 2020 Jun; 189():105275. PubMed ID: 31978805
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.
    Hsu CM; Hsu CC; Hsu ZM; Shih FY; Chang ML; Chen TH
    Sensors (Basel); 2021 Sep; 21(18):. PubMed ID: 34577209
    [TBL] [Abstract][Full Text] [Related]  

  • 16. BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis.
    Zhang E; Seiler S; Chen M; Lu W; Gu X
    Phys Med Biol; 2020 Jun; 65(12):125005. PubMed ID: 32155605
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep Learning Based One-Class Detection System for Fake Faces Generated by GAN Network.
    Li S; Dutta V; He X; Matsumaru T
    Sensors (Basel); 2022 Oct; 22(20):. PubMed ID: 36298117
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Training data enhancements for improving colonic polyp detection using deep convolutional neural networks.
    de Almeida Thomaz V; Sierra-Franco CA; Raposo AB
    Artif Intell Med; 2021 Jan; 111():101988. PubMed ID: 33461694
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Weakly supervised mitosis detection in breast histopathology images using concentric loss.
    Li C; Wang X; Liu W; Latecki LJ; Wang B; Huang J
    Med Image Anal; 2019 Apr; 53():165-178. PubMed ID: 30798116
    [TBL] [Abstract][Full Text] [Related]  

  • 20. DLGNet: A dual-branch lesion-aware network with the supervised Gaussian Mixture model for colon lesions classification in colonoscopy images.
    Wang KN; Zhuang S; Ran QY; Zhou P; Hua J; Zhou GQ; He X
    Med Image Anal; 2023 Jul; 87():102832. PubMed ID: 37148864
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.