• DocumentCode
    1922872
  • Title

    Automatic Analysis of HER-2/neu Immunohistochemistry in Breast Cancer

  • Author

    Chang, Chuan-Yu ; Huang, Ya-Chi ; Ko, Chien-Chuan

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Yunlin Univ. of Sci. & Technol., Yunlin, Taiwan
  • fYear
    2012
  • fDate
    26-28 Sept. 2012
  • Firstpage
    297
  • Lastpage
    300
  • Abstract
    Breast cancer is the second most common cancer in females, after lung cancer in the world. In Taiwan, there are about 7500 female suffering from breast cancer every year. The incidence of breast cancer has exceeded cervical cancer and has become the most common female cancer. Immunohistochemistry (IHC) image is widely applied to the diagnosis of breast cancer, but it requires a great deal of manpower and time. Therefore, in this paper, we proposed a method to assess the grade of breast cancer in IHC images. The proposed method consists of four steps, including ROI extraction, feature extraction, feature selection, and a SVM classifier. According to the experimental results, the proposed method can automatically and effectively asses the score of IHC images.
  • Keywords
    cancer; feature extraction; learning (artificial intelligence); medical image processing; support vector machines; HER-2/neu immunohistochemistry; IHC image; ROI extraction; SVM classifier; Taiwan; automatic analysis; breast cancer; cervical cancer; feature extraction; feature selection; female cancer; lung cancer; Breast cancer; Entropy; Feature extraction; Image color analysis; Immune system; Support vector machines; IHC image; ROI; SFFS; SVM classifier; breast cancer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Bio-Inspired Computing and Applications (IBICA), 2012 Third International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-1-4673-2838-8
  • Type

    conf

  • DOI
    10.1109/IBICA.2012.72
  • Filename
    6337681