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1 March 2009 Automated detection and analysis of fluorescent in situ hybridization spots depicted in digital microscopic images of Pap-smear specimens
Xingwei Wang, Bin Zheng, Shibo Li, Roy Zhang, John J. Mulvihill M.D., Wei R. Chen, Hong Liu
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Journal of Biomedical Optics, Vol. 14, Issue 2, 021002 (March 2009). https://doi.org/10.1117/1.3081545
Abstract
Fluorescence in situ hybridization (FISH) technology has been widely recognized as a promising molecular and biomedical optical imaging tool to screen and diagnose cervical cancer. However, manual FISH analysis is time-consuming and may introduce large inter-reader variability. In this study, a computerized scheme is developed and tested. It automatically detects and analyzes FISH spots depicted on microscopic fluorescence images. The scheme includes two stages: (1) a feature-based classification rule to detect useful interphase cells, and (2) a knowledge-based expert classifier to identify splitting FISH spots and improve the accuracy of counting independent FISH spots. The scheme then classifies detected analyzable cells as normal or abnormal. In this study, 150 FISH images were acquired from Pap-smear specimens and examined by both an experienced cytogeneticist and the scheme. The results showed that (1) the agreement between the cytogeneticist and the scheme was 96.9% in classifying between analyzable and unanalyzable cells (Kappa=0.917), and (2) agreements in detecting normal and abnormal cells based on FISH spots were 90.5% and 95.8% with Kappa=0.867. This study demonstrated the feasibility of automated FISH analysis, which may potentially improve detection efficiency and produce more accurate and consistent results than manual FISH analysis.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
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Xingwei Wang, Bin Zheng, Shibo Li, Roy Zhang, John J. Mulvihill M.D., Wei R. Chen, and Hong Liu "Automated detection and analysis of fluorescent in situ hybridization spots depicted in digital microscopic images of Pap-smear specimens," Journal of Biomedical Optics 14(2), 021002 (1 March 2009). https://doi.org/10.1117/1.3081545
Published: 1 March 2009
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KEYWORDS
Cervical cancer
Biological research
Visualization
Luminescence
Image segmentation
Diagnostics
Signal detection
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