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Proceedings Paper

Automated tissue m-FISH analysis workstation for identification of clonally related cells
Author(s): Piotr Dubrowski; Wan Lam; Victor Ling; Stephen Lam; Calum MacAulay
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Paper Abstract

We have developed an automated multicolour high-throughput multi-colour Fluorescence in-situ Hybridization (FISH) scanning system for examining Non-Small Cell Lung Cancer (NSCLC) 5-10μm thick tissue specimens and analyzing their FISH spot signals at the individual cell level and then as clonal populations using cell-cell architecture (spatial distributions). Using FISH probes targeting genomic areas deemed significant to chemotherapy resistance, we aim to identify clonal subpopulations of cells in tissue samples likely to be resistant to cis-platinum/vinorelbine chemotherapy. The scanning system consists of automatic image acquisition, cell nuclei segmentation, spot counting and measuring the spatial distribution and connectivity of cells with specific genetic profiles across the entire section using architectural tools to provide the scoring system.

Paper Details

Date Published: 29 February 2008
PDF: 12 pages
Proc. SPIE 6859, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VI, 68591T (29 February 2008); doi: 10.1117/12.763519
Show Author Affiliations
Piotr Dubrowski, British Columbia Cancer Agency (Canada)
Wan Lam, British Columbia Cancer Agency (Canada)
Victor Ling, British Columbia Cancer Agency (Canada)
Stephen Lam, British Columbia Cancer Agency (Canada)
Calum MacAulay, British Columbia Cancer Agency (Canada)


Published in SPIE Proceedings Vol. 6859:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VI
Daniel L. Farkas; Dan V. Nicolau; Robert C. Leif, Editor(s)

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