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
Link To Document :
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