Experimental Image Sets

Calculation of the CRLB using Experimental Image Sets

Post Title

Introduction

The best possible accuracy with which an object of interest can be localized when imaged using a fuorescence microscope is typically calculated using the Cramer-Rao lower bound (CRLB). The calculation of the CRLB, however, so far relied on an analytical expression for the image of the object. This can pose challenges in practice since it is often difficult to find appropriate analytical models for the images of general objects. Even if an appropriate analytical model is available, the lack of knowledge about the precise values of imaging parameters might also impose difficulties in the calculation of the CRLB. To address these challenges, we have developed an approach that directly uses an experimentally collected image set to calculate the best possible localization accuracy for a general subcellular object. In this approach, we fit smoothly connected piecewise polynomials, known as splines, to the experimentally collected image set to provide a continuous model of the object. This continuous model can then be used for the calculation of the best possible localization accuracy.


Software

  • Software developed in MATLAB (Optimization Toolbox, Image Processing Toolbox)
  • Based on object-oriented programming (has a graphical user interface)

Related publications

1
IF 3.488
A. Tahmasbi, E. S. Ward, and R. J. Ober, "Determination of localization accuracy based on experimentally acquired image sets: applications to single molecule microscopy," Optics Express, vol. 23, no. 6, pp. 7630-7652, 2015.
2
BMES
A. Tahmasbi, E. S. Ward, and R. J. Ober, "Localization accuracy in fluorescence microscopy based on experimentally acquired image sets," BMES Annual Meeting, Tampa Convention Center, Tampa, FL, October 7, 2015.
3
SPIE
A. Tahmasbi, E. S. Ward, and R. J. Ober, "New results on the single molecule localization problem in two and three dimensions," in Proc. SPIE, Nanoimaging and Nanospectroscopy III, 9554: 955402, San Diego, CA, August 9, 2015.

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