• DocumentCode
    1233409
  • Title

    Regional Admittivity Spectra With Tomosynthesis Images for Breast Cancer Detection: Preliminary Patient Study

  • Author

    Kao, Tzu-Jen ; Boverman, Gregory ; Kim, Bong Seok ; Isaacson, David ; Saulnier, Gary J. ; Newell, Jonathan C. ; Choi, Myoung H. ; Moore, Richard H. ; Kopans, Daniel B.

  • Author_Institution
    Dept. of Biomed. Eng., Rensselaer Polytech. Inst., Troy, NY
  • Volume
    27
  • Issue
    12
  • fYear
    2008
  • Firstpage
    1762
  • Lastpage
    1768
  • Abstract
    It has been known for some time that many tumors have a significantly different conductivity and permittivity from surrounding normal tissue. This high ldquocontrastrdquo in tissue electrical properties, occurring between a few kilohertz and several megahertz, may permit differentiating malignant from benign tissues. Here we show the ability of electrical impedance spectroscopy (EIS) to roughly localize and clearly distinguish cancers from normal tissues and benign lesions. Localization of these lesions is confirmed by simultaneous, in register digital breast tomosynthesis (DBT) mammography or 3-D mammograms.
  • Keywords
    biological organs; biomedical measurement; cancer; electric impedance imaging; mammography; tumours; benign lesion; breast cancer detection; conductivity; digital breast tomosynthesis; electrical impedance spectroscopy; electrical impedance tomography; mammography; permittivity; regional admittivity spectra; tissue electrical properties; tumors; Biomedical engineering; Breast cancer; Breast neoplasms; Breast tumors; Cancer detection; Electrochemical impedance spectroscopy; Lesions; Mammography; Surface impedance; Tomography; Breast cancer detection; breast cancer detection; digital breast tomosynthesis (DBT) mammography; digital breast tomosynthesis mammography; electrical impedance spectroscopy; electrical impedance spectroscopy (EIS); electrical impedance tomography; electrical impedance tomography (EIT); Algorithms; Breast Neoplasms; Electric Impedance; Female; Humans; Image Processing, Computer-Assisted; Linear Models; Mammography; Predictive Value of Tests; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Tomography;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2008.926049
  • Filename
    4530643