• DocumentCode
    1592362
  • Title

    Computerized Classification Method for Differentiating Between Benign and Malignant Lesions on Breast MR Images

  • Author

    Wang, Hui ; Huo, Zhimin ; Zhang, Jiwu

  • Author_Institution
    Health Group Global R&D Center, Eastman Kodak Co., Shanghai
  • fYear
    2006
  • Firstpage
    6950
  • Lastpage
    6952
  • Abstract
    Contrast-enhanced breast MRI has been shown to have very high sensitivity in the detection of breast cancers. A new computerized classification method for differentiating between benign and malignant lesions on breast MRIs was developed. This method was based on temporal feature analysis. We experimented with a set of thresholds of the contrast uptake and washout speed to automatically determine suspicious malignant areas. An angiogenesis map was generated to indicate suspicious malignant areas by color. The results obtained from the retrospective analysis on 64 malignant and 29 benign breast lesions showed that our method achieved 90.5% (57/63) sensitivity in detecting malignant lesions, and it correctly classified 55% (16/29) benign lesions as benign. The study results demonstrated the effectiveness of this temporal feature analysis method for the detection of malignant lesions and its performance in delineating malignant lesions from benign lesions
  • Keywords
    biological organs; biomedical MRI; cancer; gynaecology; image classification; medical image processing; tumours; angiogenesis map; benign lesions; breast cancers; computerized classification; contrast uptake; contrast-enhanced breast MRI; malignant lesions; temporal feature analysis; washout speed; Biopsy; Breast; Cancer; Image analysis; Kinetic theory; Lesions; Magnetic resonance imaging; Performance analysis; Research and development; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1616104
  • Filename
    1616104