BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

152 related articles for article (PubMed ID: 34911147)

  • 1. Development of novel deep multimodal representation learning-based model for the differentiation of liver tumors on B-mode ultrasound images.
    Sato M; Kobayashi T; Soroida Y; Tanaka T; Nakatsuka T; Nakagawa H; Nakamura A; Kurihara M; Endo M; Hikita H; Sato M; Gotoh H; Iwai T; Tateishi R; Koike K; Yatomi Y
    J Gastroenterol Hepatol; 2022 Apr; 37(4):678-684. PubMed ID: 34911147
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B.
    Liu Z; Li W; Zhu Z; Wen H; Li MD; Hou C; Shen H; Huang B; Luo Y; Wang W; Chen X
    Eur Radiol; 2023 Aug; 33(8):5871-5881. PubMed ID: 36735040
    [TBL] [Abstract][Full Text] [Related]  

  • 3. B-mode ultrasound based CAD for liver cancers via multi-view privileged information learning.
    Han X; Gong B; Guo L; Wang J; Ying S; Li S; Shi J
    Neural Netw; 2023 Jul; 164():369-381. PubMed ID: 37167750
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study.
    Yasaka K; Akai H; Abe O; Kiryu S
    Radiology; 2018 Mar; 286(3):887-896. PubMed ID: 29059036
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.
    Yoo TK; Choi JY; Seo JG; Ramasubramanian B; Selvaperumal S; Kim DW
    Med Biol Eng Comput; 2019 Mar; 57(3):677-687. PubMed ID: 30349958
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Improving B-mode ultrasound diagnostic performance for focal liver lesions using deep learning: A multicentre study.
    Yang Q; Wei J; Hao X; Kong D; Yu X; Jiang T; Xi J; Cai W; Luo Y; Jing X; Yang Y; Cheng Z; Wu J; Zhang H; Liao J; Zhou P; Song Y; Zhang Y; Han Z; Cheng W; Tang L; Liu F; Dou J; Zheng R; Yu J; Tian J; Liang P
    EBioMedicine; 2020 Jun; 56():102777. PubMed ID: 32485640
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Liver disease classification from ultrasound using multi-scale CNN.
    Che H; Brown LG; Foran DJ; Nosher JL; Hacihaliloglu I
    Int J Comput Assist Radiol Surg; 2021 Sep; 16(9):1537-1548. PubMed ID: 34097226
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Detection and Monitoring of Thermal Lesions Induced by Microwave Ablation Using Ultrasound Imaging and Convolutional Neural Networks.
    Zhang S; Wu S; Shang S; Qin X; Jia X; Li D; Cui Z; Xu T; Niu G; Bouakaz A; Wan M
    IEEE J Biomed Health Inform; 2020 Apr; 24(4):965-973. PubMed ID: 31502996
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.
    Xue LY; Jiang ZY; Fu TT; Wang QM; Zhu YL; Dai M; Wang WP; Yu JH; Ding H
    Eur Radiol; 2020 May; 30(5):2973-2983. PubMed ID: 31965257
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Decoding the molecular subtypes of breast cancer seen on multimodal ultrasound images using an assembled convolutional neural network model: A prospective and multicentre study.
    Zhou BY; Wang LF; Yin HH; Wu TF; Ren TT; Peng C; Li DX; Shi H; Sun LP; Zhao CK; Xu HX
    EBioMedicine; 2021 Dec; 74():103684. PubMed ID: 34773890
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Grading of hepatocellular carcinoma based on diffusion weighted images with multiple b-values using convolutional neural networks.
    Zhou W; Wang G; Xie G; Zhang L
    Med Phys; 2019 Sep; 46(9):3951-3960. PubMed ID: 31169907
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods.
    Mitrea D; Badea R; Mitrea P; Brad S; Nedevschi S
    Sensors (Basel); 2021 Mar; 21(6):. PubMed ID: 33801125
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning-based multimodal fusion network for segmentation and classification of breast cancers using B-mode and elastography ultrasound images.
    Misra S; Yoon C; Kim KJ; Managuli R; Barr RG; Baek J; Kim C
    Bioeng Transl Med; 2023 Nov; 8(6):e10480. PubMed ID: 38023698
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.
    Gong H; Yu L; Leng S; Dilger SK; Ren L; Zhou W; Fletcher JG; McCollough CH
    Med Phys; 2019 May; 46(5):2052-2063. PubMed ID: 30889282
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis.
    Cepeda S; García-García S; Arrese I; Fernández-Pérez G; Velasco-Casares M; Fajardo-Puentes M; Zamora T; Sarabia R
    Front Oncol; 2020; 10():590756. PubMed ID: 33604286
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep learning for the diagnosis of suspicious thyroid nodules based on multimodal ultrasound images.
    Tao Y; Yu Y; Wu T; Xu X; Dai Q; Kong H; Zhang L; Yu W; Leng X; Qiu W; Tian J
    Front Oncol; 2022; 12():1012724. PubMed ID: 36425556
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.
    Yagasaki S; Koizumi N; Nishiyama Y; Kondo R; Imaizumi T; Matsumoto N; Ogawa M; Numata K
    Int J Comput Assist Radiol Surg; 2020 Dec; 15(12):1989-1995. PubMed ID: 33009985
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images.
    Brehar R; Mitrea DA; Vancea F; Marita T; Nedevschi S; Lupsor-Platon M; Rotaru M; Badea RI
    Sensors (Basel); 2020 May; 20(11):. PubMed ID: 32485986
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network.
    Lee JH; Joo I; Kang TW; Paik YH; Sinn DH; Ha SY; Kim K; Choi C; Lee G; Yi J; Bang WC
    Eur Radiol; 2020 Feb; 30(2):1264-1273. PubMed ID: 31478087
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.