• DocumentCode
    2367355
  • Title

    Stepwise logistic regression analysis of tumor contour features for breast ultrasound diagnosis

  • Author

    Chiang, Huihua K. ; Chui-Mei Tiu ; Chang, T.Y. ; Yi-Hong Chou

  • Author_Institution
    Inst. of Biomed. Eng., Nat. Yang Ming Univ., Taipei
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1303
  • Abstract
    To assist the ultrasound diagnosis of solid breast tumors by using stepwise logistic regression (SLR) analysis of tumor contour features, we reviewed 111 digitized US images of breast tumors. They were 40 benign breast tumors (fibroadenomas), and 71 infiltrative ductal carcinomas. The contour features were calculated by the radial length. A SLR model with contour features was used to classify tumors as benign or malignant. The accuracy of our model with contour features for classifying malignancies was 91.0% (101 of 111 tumors), the sensitivity was 97.2% (69 of 71), the specificity was 80.0% (32 of 40)
  • Keywords
    biomedical ultrasonics; feature extraction; image classification; mammography; medical image processing; probability; statistical analysis; tumours; CAD system; benign tumors; boundary roughness; differential diagnosis; digitized US images; entropy; features extraction; fibroadenomas; forward stepwise procedure; infiltrative ductal carcinomas; radial length; solid breast tumors; stepwise logistic regression analysis; tumor circularity; tumor classification; tumor contour features; tumor malignancy probability; ultrasound diagnosis; Breast neoplasms; Breast tumors; Cancer; Entropy; Feature extraction; Logistics; Malignant tumors; Regression analysis; Solids; Ultrasonic imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ultrasonics Symposium, 2001 IEEE
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7803-7177-1
  • Type

    conf

  • DOI
    10.1109/ULTSYM.2001.991959
  • Filename
    991959