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Connection

Bin Zheng to Radiographic Image Interpretation, Computer-Assisted

This is a "connection" page, showing publications Bin Zheng has written about Radiographic Image Interpretation, Computer-Assisted.
  1. Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk. Phys Med Biol. 2018 05 15; 63(10):105005.
    View in: PubMed
    Score: 0.574
  2. Classification of Breast Masses Using a Computer-Aided Diagnosis Scheme of Contrast Enhanced Digital Mammograms. Ann Biomed Eng. 2018 Sep; 46(9):1419-1431.
    View in: PubMed
    Score: 0.573
  3. Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm. Phys Med Biol. 2018 01 30; 63(3):035020.
    View in: PubMed
    Score: 0.563
  4. Computer-aided classification of mammographic masses using visually sensitive image features. J Xray Sci Technol. 2017; 25(1):171-186.
    View in: PubMed
    Score: 0.522
  5. Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions. Phys Med Biol. 2017 01 21; 62(2):358-376.
    View in: PubMed
    Score: 0.521
  6. Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis. Acta Radiol. 2016 Sep; 57(9):1149-55.
    View in: PubMed
    Score: 0.485
  7. Assessment of performance and reproducibility of applying a content-based image retrieval scheme for classification of breast lesions. Med Phys. 2015 Jul; 42(7):4241-9.
    View in: PubMed
    Score: 0.470
  8. A new approach to develop computer-aided detection schemes of digital mammograms. Phys Med Biol. 2015 Jun 07; 60(11):4413-27.
    View in: PubMed
    Score: 0.466
  9. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme. Med Phys. 2014 Aug; 41(8):081906.
    View in: PubMed
    Score: 0.441
  10. Reduction of false-positive recalls using a computerized mammographic image feature analysis scheme. Phys Med Biol. 2014 Aug 07; 59(15):4357-73.
    View in: PubMed
    Score: 0.440
  11. Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer. Comput Methods Programs Biomed. 2019 Oct; 179:104995.
    View in: PubMed
    Score: 0.156
  12. Noise Power Characteristics of a Micro-Computed Tomography System. J Comput Assist Tomogr. 2017 Jan; 41(1):82-89.
    View in: PubMed
    Score: 0.130
  13. The impact of spectral filtration on image quality in micro-CT system. J Appl Clin Med Phys. 2016 01 08; 17(1):301-315.
    View in: PubMed
    Score: 0.122
  14. Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model. Int J Comput Assist Radiol Surg. 2014 Nov; 9(6):1005-20.
    View in: PubMed
    Score: 0.108
  15. Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry. Acad Radiol. 2013 Dec; 20(12):1542-50.
    View in: PubMed
    Score: 0.105
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.

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