BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

268 related articles for article (PubMed ID: 33409774)

  • 1. Thyroid nodule recognition using a joint convolutional neural network with information fusion of ultrasound images and radiofrequency data.
    Liu Z; Zhong S; Liu Q; Xie C; Dai Y; Peng C; Chen X; Zou R
    Eur Radiol; 2021 Jul; 31(7):5001-5011. PubMed ID: 33409774
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound.
    Ko SY; Lee JH; Yoon JH; Na H; Hong E; Han K; Jung I; Kim EK; Moon HJ; Park VY; Lee E; Kwak JY
    Head Neck; 2019 Apr; 41(4):885-891. PubMed ID: 30715773
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images.
    Zhou H; Jin Y; Dai L; Zhang M; Qiu Y; Wang K; Tian J; Zheng J
    Eur J Radiol; 2020 Jun; 127():108992. PubMed ID: 32339983
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Convolutional Neural Network for Predicting Thyroid Cancer Based on Ultrasound Elastography Image of Perinodular Region.
    Hu L; Pei C; Xie L; Liu Z; He N; Lv W
    Endocrinology; 2022 Oct; 163(11):. PubMed ID: 35971296
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images.
    Ma J; Wu F; Jiang T; Zhu J; Kong D
    Med Phys; 2017 May; 44(5):1678-1691. PubMed ID: 28186630
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network.
    Wang L; Yang S; Yang S; Zhao C; Tian G; Gao Y; Chen Y; Lu Y
    World J Surg Oncol; 2019 Jan; 17(1):12. PubMed ID: 30621704
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network.
    Chi J; Walia E; Babyn P; Wang J; Groot G; Eramian M
    J Digit Imaging; 2017 Aug; 30(4):477-486. PubMed ID: 28695342
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Ensemble Deep Learning Model for Multicenter Classification of Thyroid Nodules on Ultrasound Images.
    Wei X; Gao M; Yu R; Liu Z; Gu Q; Liu X; Zheng Z; Zheng X; Zhu J; Zhang S
    Med Sci Monit; 2020 Jun; 26():e926096. PubMed ID: 32555130
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks.
    Wang L; Zhang L; Zhu M; Qi X; Yi Z
    Med Image Anal; 2020 Apr; 61():101665. PubMed ID: 32062156
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Ultrasound-based differentiation of malignant and benign thyroid Nodules: An extreme learning machine approach.
    Xia J; Chen H; Li Q; Zhou M; Chen L; Cai Z; Fang Y; Zhou H
    Comput Methods Programs Biomed; 2017 Aug; 147():37-49. PubMed ID: 28734529
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images.
    Sun C; Zhang Y; Chang Q; Liu T; Zhang S; Wang X; Guo Q; Yao J; Sun W; Niu L
    Med Phys; 2020 Sep; 47(9):3952-3960. PubMed ID: 32473030
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A pre-trained convolutional neural network based method for thyroid nodule diagnosis.
    Ma J; Wu F; Zhu J; Xu D; Kong D
    Ultrasonics; 2017 Jan; 73():221-230. PubMed ID: 27668999
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Semi-supervised graph convolutional networks for the domain adaptive recognition of thyroid nodules in cross-device ultrasound images.
    Zhang K; Li Z; Cai C; Liu J; Xu D; Fang C; Huang P; Wang Y; Yang M; Chang S
    Med Phys; 2023 Dec; 50(12):7806-7821. PubMed ID: 36967664
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Diagnosis of Benign and Malignant Thyroid Nodules Using Combined Conventional Ultrasound and Ultrasound Elasticity Imaging.
    Qin P; Wu K; Hu Y; Zeng J; Chai X
    IEEE J Biomed Health Inform; 2020 Apr; 24(4):1028-1036. PubMed ID: 31689223
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Ultrasonographic Thyroid Nodule Classification Using a Deep Convolutional Neural Network with Surgical Pathology.
    Kwon SW; Choi IJ; Kang JY; Jang WI; Lee GH; Lee MC
    J Digit Imaging; 2020 Oct; 33(5):1202-1208. PubMed ID: 32705433
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automated detection and classification of thyroid nodules in ultrasound images using clinical-knowledge-guided convolutional neural networks.
    Liu T; Guo Q; Lian C; Ren X; Liang S; Yu J; Niu L; Sun W; Shen D
    Med Image Anal; 2019 Dec; 58():101555. PubMed ID: 31520984
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Patch-based classification of thyroid nodules in ultrasound images using direction independent features extracted by two-threshold binary decomposition.
    Prochazka A; Gulati S; Holinka S; Smutek D
    Comput Med Imaging Graph; 2019 Jan; 71():9-18. PubMed ID: 30453231
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Online Transfer Learning for Differential Diagnosis of Benign and Malignant Thyroid Nodules With Ultrasound Images.
    Zhou H; Wang K; Tian J
    IEEE Trans Biomed Eng; 2020 Oct; 67(10):2773-2780. PubMed ID: 32011998
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An intelligent platform for ultrasound diagnosis of thyroid nodules.
    Ye H; Hang J; Chen X; Di Xu ; Chen J; Ye X; Zhang D
    Sci Rep; 2020 Aug; 10(1):13223. PubMed ID: 32764673
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study.
    Li X; Zhang S; Zhang Q; Wei X; Pan Y; Zhao J; Xin X; Qin C; Wang X; Li J; Yang F; Zhao Y; Yang M; Wang Q; Zheng Z; Zheng X; Yang X; Whitlow CT; Gurcan MN; Zhang L; Wang X; Pasche BC; Gao M; Zhang W; Chen K
    Lancet Oncol; 2019 Feb; 20(2):193-201. PubMed ID: 30583848
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.