BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

128 related articles for article (PubMed ID: 34087829)

  • 1. Identify the triple-negative and non-triple-negative breast cancer by using texture features of medicale ultrasonic image: A STROBE-compliant study.
    Chen Q; Xia J; Zhang J
    Medicine (Baltimore); 2021 Jun; 100(22):e25878. PubMed ID: 34087829
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A pilot study of radiomics technology based on X-ray mammography in patients with triple-negative breast cancer.
    Zhang HX; Sun ZQ; Cheng YG; Mao GQ
    J Xray Sci Technol; 2019; 27(3):485-492. PubMed ID: 31081797
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer-aided diagnosis for distinguishing between triple-negative breast cancer and fibroadenomas based on ultrasound texture features.
    Moon WK; Huang YS; Lo CM; Huang CS; Bae MS; Kim WH; Chen JH; Chang RF
    Med Phys; 2015 Jun; 42(6):3024-35. PubMed ID: 26127055
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Identification of triple-negative breast cancer and androgen receptor expression based on histogram and texture analysis of dynamic contrast-enhanced MRI.
    Xu WJ; Zheng BJ; Lu J; Liu SY; Li HL
    BMC Med Imaging; 2023 Jun; 23(1):70. PubMed ID: 37264313
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer.
    Soussan M; Orlhac F; Boubaya M; Zelek L; Ziol M; Eder V; Buvat I
    PLoS One; 2014; 9(4):e94017. PubMed ID: 24722644
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Minkowski functionals: An MRI texture analysis tool for determination of the aggressiveness of breast cancer.
    Fox MJ; Gibbs P; Pickles MD
    J Magn Reson Imaging; 2016 Apr; 43(4):903-10. PubMed ID: 26453892
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Radiomics of US texture features in differential diagnosis between triple-negative breast cancer and fibroadenoma.
    Lee SE; Han K; Kwak JY; Lee E; Kim EK
    Sci Rep; 2018 Sep; 8(1):13546. PubMed ID: 30202040
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomic analysis on magnetic resonance diffusion weighted image in distinguishing triple-negative breast cancer from other subtypes: a feasibility study.
    Wang Q; Mao N; Liu M; Shi Y; Ma H; Dong J; Zhang X; Duan S; Wang B; Xie H
    Clin Imaging; 2021 Apr; 72():136-141. PubMed ID: 33242692
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Quantification of breast tumor heterogeneity for ER status, HER2 status, and TN molecular subtype evaluation on DCE-MRI.
    Chang RF; Chen HH; Chang YC; Huang CS; Chen JH; Lo CM
    Magn Reson Imaging; 2016 Jul; 34(6):809-819. PubMed ID: 26968141
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Diagnosis of triple negative breast cancer based on radiomics signatures extracted from preoperative contrast-enhanced chest computed tomography.
    Feng Q; Hu Q; Liu Y; Yang T; Yin Z
    BMC Cancer; 2020 Jun; 20(1):579. PubMed ID: 32571245
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine learning for diagnostic ultrasound of triple-negative breast cancer.
    Wu T; Sultan LR; Tian J; Cary TW; Sehgal CM
    Breast Cancer Res Treat; 2019 Jan; 173(2):365-373. PubMed ID: 30343454
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Systematic Review and Meta-analysis of the Malignant Ultrasound Features of Triple-Negative Breast Cancer.
    Tian L; Wang L; Qin Y; Cai J
    J Ultrasound Med; 2020 Oct; 39(10):2013-2025. PubMed ID: 32339328
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis.
    Li JW; Cao YC; Zhao ZJ; Shi ZT; Duan XQ; Chang C; Chen JG
    Eur Radiol; 2022 Mar; 32(3):1590-1600. PubMed ID: 34519862
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Differences in Multi-Modal Ultrasound Imaging between Triple Negative and Non-Triple Negative Breast Cancer.
    Li Z; Tian J; Wang X; Wang Y; Wang Z; Zhang L; Jing H; Wu T
    Ultrasound Med Biol; 2016 Apr; 42(4):882-90. PubMed ID: 26786891
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Features from Computerized Texture Analysis of Breast Cancers at Pretreatment MR Imaging Are Associated with Response to Neoadjuvant Chemotherapy.
    Chamming's F; Ueno Y; Ferré R; Kao E; Jannot AS; Chong J; Omeroglu A; Mesurolle B; Reinhold C; Gallix B
    Radiology; 2018 Feb; 286(2):412-420. PubMed ID: 28980886
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Ultrasound-based comparative analysis and nomogram development for predicting triple-negative and non-triple-negative breast cancer: a 4-year institutional study in Quanzhou First Hospital.
    Su L; Xie Q; Chen J; Zhang Q; Li N; Hong C
    BMJ Open; 2024 Jun; 14(6):e085340. PubMed ID: 38871659
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Texture feature analysis for breast ultrasound image enhancement.
    Liao YY; Wu JC; Li CH; Yeh CK
    Ultrason Imaging; 2011 Oct; 33(4):264-78. PubMed ID: 22518956
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Application of mammography-based radiomics signature for preoperative prediction of triple-negative breast cancer.
    Ge S; Yixing Y; Jia D; Ling Y
    BMC Med Imaging; 2022 Sep; 22(1):166. PubMed ID: 36104679
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Breast tumor classification using different features of quantitative ultrasound parametric images.
    Hsu SM; Kuo WH; Kuo FC; Liao YY
    Int J Comput Assist Radiol Surg; 2019 Apr; 14(4):623-633. PubMed ID: 30617720
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.
    Li Z; Yu L; Wang X; Yu H; Gao Y; Ren Y; Wang G; Zhou X
    Clin Breast Cancer; 2018 Aug; 18(4):e621-e627. PubMed ID: 29199085
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.