• DocumentCode
    1395257
  • Title

    Computer-aided detection of breast cancer nuclei

  • Author

    Schnorrenberg, Frank ; Pattichis, Constantinos S. ; Kyriacou, Kyriacos C. ; Schizas, Christos N.

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
  • Volume
    1
  • Issue
    2
  • fYear
    1997
  • fDate
    6/1/1997 12:00:00 AM
  • Firstpage
    128
  • Lastpage
    140
  • Abstract
    A computer-aided detection system for tissue cell nuclei in histological sections is introduced and validated as part of the Biopsy Analysis Support System (BASS). Cell nuclei are selectively stained with monoclonal antibodies, such as the anti-estrogen receptor antibodies, which are widely applied as part of assessing patient prognosis in breast cancer. The detection system uses a receptive field filter to enhance negatively and positively stained cell nuclei and a squashing function to label each pixel value as belonging to the background or a nucleus. In this study, the detection system assessed all biopsies in an automated fashion. Detection and classification of individual nuclei as well as biopsy grading performance was shown to be promising as compared to that of two experts. Sensitivity and positive predictive value were measured to be 83% and 67.4%, respectively. One major advantage of BASS stems from the fact that the system simulates the assessment procedures routinely employed by human experts; thus it can be used as an additional independent expert. Moreover, the system allows the efficient accumulation of data from large numbers of nuclei in a short time span. Therefore, the potential for accurate quantitative assessments is increased and a platform for more standardized evaluations is provided.
  • Keywords
    image classification; image enhancement; medical image processing; BASS; Biopsy Analysis Support System; accurate quantitative assessment; anti-estrogen receptor antibodies; biopsy grading performance; breast cancer; computer-aided detection system; histological sections; monoclonal antibodies; patient prognosis assessment; pixel value labeling; positive predictive value; receptive field filter; selective staining; sensitivity; squashing function; standardized evaluations; tissue cell nuclei; Biopsy; Breast cancer; Cancer detection; Diseases; Filters; Genetics; Humans; Immune system; Nervous system; Tumors; Algorithms; Breast Neoplasms; Cell Nucleus; Diagnosis, Computer-Assisted; Female; Humans; Receptors, Estrogen; Receptors, Progesterone;
  • fLanguage
    English
  • Journal_Title
    Information Technology in Biomedicine, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1089-7771
  • Type

    jour

  • DOI
    10.1109/4233.640655
  • Filename
    640655