BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

177 related articles for article (PubMed ID: 21482168)

  • 1. Computerized prediction of risk for developing breast cancer based on bilateral mammographic breast tissue asymmetry.
    Wang X; Lederman D; Tan J; Wang XH; Zheng B
    Med Eng Phys; 2011 Oct; 33(8):934-42. PubMed ID: 21482168
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Computerized detection of breast tissue asymmetry depicted on bilateral mammograms: a preliminary study of breast risk stratification.
    Wang X; Lederman D; Tan J; Wang XH; Zheng B
    Acad Radiol; 2010 Oct; 17(10):1234-41. PubMed ID: 20619697
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer.
    Chen X; Zargari A; Hollingsworth AB; Liu H; Zheng B; Qiu Y
    Comput Methods Programs Biomed; 2019 Oct; 179():104995. PubMed ID: 31443864
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk.
    Li Y; Fan M; Cheng H; Zhang P; Zheng B; Li L
    Phys Med Biol; 2018 Jan; 63(2):025004. PubMed ID: 29226849
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving performance of computer-aided detection of masses by incorporating bilateral mammographic density asymmetry: an assessment.
    Wang X; Li L; Xu W; Liu W; Lederman D; Zheng B
    Acad Radiol; 2012 Mar; 19(3):303-10. PubMed ID: 22173323
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fusion of k-Gabor features from medio-lateral-oblique and craniocaudal view mammograms for improved breast cancer diagnosis.
    Sasikala S; Ezhilarasi M
    J Cancer Res Ther; 2018; 14(5):1036-1041. PubMed ID: 30197344
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.
    Heidari M; Khuzani AZ; Hollingsworth AB; Danala G; Mirniaharikandehei S; Qiu Y; Liu H; Zheng B
    Phys Med Biol; 2018 Jan; 63(3):035020. PubMed ID: 29239858
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk.
    Tan M; Pu J; Cheng S; Liu H; Zheng B
    Ann Biomed Eng; 2015 Oct; 43(10):2416-28. PubMed ID: 25851469
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Association between computed tissue density asymmetry in bilateral mammograms and near-term breast cancer risk.
    Zheng B; Tan M; Ramalingam P; Gur D
    Breast J; 2014; 20(3):249-57. PubMed ID: 24673749
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions.
    Tan M; Aghaei F; Wang Y; Zheng B
    Phys Med Biol; 2017 Jan; 62(2):358-376. PubMed ID: 27997380
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A new approach to develop computer-aided detection schemes of digital mammograms.
    Tan M; Qian W; Pu J; Liu H; Zheng B
    Phys Med Biol; 2015 Jun; 60(11):4413-27. PubMed ID: 25984710
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme.
    Tan M; Pu J; Zheng B
    Med Phys; 2014 Aug; 41(8):081906. PubMed ID: 25086537
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry.
    Tan M; Zheng B; Ramalingam P; Gur D
    Acad Radiol; 2013 Dec; 20(12):1542-50. PubMed ID: 24200481
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Reduction of false-positive recalls using a computerized mammographic image feature analysis scheme.
    Tan M; Pu J; Zheng B
    Phys Med Biol; 2014 Aug; 59(15):4357-73. PubMed ID: 25029964
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction.
    Yan S; Wang Y; Aghaei F; Qiu Y; Zheng B
    Int J Comput Assist Radiol Surg; 2017 Oct; 12(10):1819-1828. PubMed ID: 28726117
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Determination of mammographic breast density using a deep convolutional neural network.
    Ciritsis A; Rossi C; Vittoria De Martini I; Eberhard M; Marcon M; Becker AS; Berger N; Boss A
    Br J Radiol; 2019 Jan; 92(1093):20180691. PubMed ID: 30209957
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Bilateral mammographic density asymmetry and breast cancer risk: a preliminary assessment.
    Zheng B; Sumkin JH; Zuley ML; Wang X; Klym AH; Gur D
    Eur J Radiol; 2012 Nov; 81(11):3222-8. PubMed ID: 22579527
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A new computer-aided detection approach based on analysis of local and global mammographic feature asymmetry.
    Kelder A; Lederman D; Zheng B; Zigel Y
    Med Phys; 2018 Apr; 45(4):1459-1470. PubMed ID: 29431858
    [TBL] [Abstract][Full Text] [Related]  

  • 19. External validation of a publicly available computer assisted diagnostic tool for mammographic mass lesions with two high prevalence research datasets.
    Benndorf M; Burnside ES; Herda C; Langer M; Kotter E
    Med Phys; 2015 Aug; 42(8):4987-96. PubMed ID: 26233224
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Improving Performance of Breast Cancer Risk Prediction by Incorporating Optical Density Image Feature Analysis: An Assessment.
    Yan S; Wang Y; Aghaei F; Qiu Y; Zheng B
    Acad Radiol; 2022 Jan; 29 Suppl 1(Suppl 1):S199-S210. PubMed ID: 28985925
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.