DocumentCode
1760462
Title
Performance Analysis and Design of Position-Encoded Microsphere Arrays Using the Ziv-Zakai Bound
Author
Xiaoxiao Xu ; Sarder, P. ; Kotagiri, N. ; Achilefu, Samuel ; Nehorai, Arye
Author_Institution
Preston M. Green Dept. of Electr. & Syst. Eng., Washington Univ. in St. Louis, St. Louis, MO, USA
Volume
12
Issue
1
fYear
2013
fDate
41334
Firstpage
29
Lastpage
40
Abstract
Position-encoded microsphere arrays are a promising technology for identifying biological targets and quantifying their concentrations. In this paper we analyze the statistical performance of these arrays in imaging targets at typical low signal-to-noise ratio (SNR) levels. We compute the Ziv-Zakai bound (ZZB) on the errors in estimating the unknown parameters, including the target concentrations. We find the SNR level below which the ZZB provides a more accurate prediction of the error than the posterior Cramér-Rao bound (PCRB), through numerical examples. We further apply the ZZB to select the optimal design parameters of the microsphere array device and investigate the effects of the experimental variables such as microscope point-spread function. An imaging experiment on microspheres with protein targets verifies the optimal design parameters using the ZZB.
Keywords
encoding; estimation theory; fluorescence; lab-on-a-chip; molecular biophysics; optical microscopy; optical transfer function; proteins; statistical analysis; Ziv-Zakai bound; biological targets; microscope point-spread function; microsphere array device; optimal design parameters; position-encoded microsphere array design; posterior Cramer-Rao bound; protein targets; signal-to-noise ratio levels; statistical performance analysis; Estimation; Microscopy; Noise measurement; Performance evaluation; Signal to noise ratio; Microscope point-spread function; Ziv-Zakai bound; optimal design; position-encoded microsphere arrays; posterior Cramér-Rao bound; Biological Assay; Biotechnology; Computer Simulation; Microarray Analysis; Microspheres; Models, Statistical; Nanotechnology; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio;
fLanguage
English
Journal_Title
NanoBioscience, IEEE Transactions on
Publisher
ieee
ISSN
1536-1241
Type
jour
DOI
10.1109/TNB.2012.2230116
Filename
6384802
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