• DocumentCode
    2477417
  • Title

    Quantification of Subcellular Molecules in Tissue Microarray

  • Author

    Can, Ali ; Bello, Musodiq O. ; Gerdes, Michael J.

  • Author_Institution
    GE Global Res. Center, Niskayuna, NY, USA
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    2548
  • Lastpage
    2551
  • Abstract
    Quantifying expression levels of proteins with sub cellular resolution is critical to many applications ranging from biomarker discovery to treatment planning. In this paper, we present a fully automated method and a new metric that quantifies the expression of target proteins in immunohisto-chemically stained tissue microarray (TMA) samples. The proposed metric is superior to existing intensity or ratio-based methods. We compared performance with the majority decision of a group of 19 observers scoring estrogen receptor (ER) status, achieving a detection rate of 96% with 90% specificity. The presented methods will accelerate the processes of biomarker discovery and transitioning of biomarkers from research bench to clinical utility.
  • Keywords
    biology computing; TMA; biomarker discovery; estrogen receptor; ratio based methods; sub cellular resolution; subcellular molecules quantification; tissue microarray; treatment planning; Biological tissues; Biomembranes; Erbium; Immune system; Measurement; Observers; Proteins; Automated Biomarker Scoring; Biomarker quantification; Fluorescent Microscopy Image Analysis; Molecular Cell Imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.624
  • Filename
    5595789