Abstract:
:Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Arce SH,Wu PH,Tseng Ydoi
10.1038/srep02266subject
Has Abstractpub_date
2013-01-01 00:00:00pages
2266issn
2045-2322pii
srep02266journal_volume
3pub_type
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