Cramér-Rao Lower Bound for Point Based Image Registration With Heteroscedastic Error Model for Application in Single Molecule Microscopy

Effect of Pixelation on the Parameter Estimation of Single Molecule Trajectories

The advent of single molecule microscopy has revolutionized biological investigations by providing a powerful tool for the study of intercellular and intracellular trafficking processes of protein molecules which was not available before through conventional microscopy. In practice, pixelated detectors are used to acquire the images of fluorescently labeled objects moving in cellular environments. Then, the acquired fluorescence microscopy images contain the numbers of the photons detected in each pixel, during an exposure time interval. Moreover, instead of having the exact locations of detection of the photons, we only know the pixel areas in which the photons impact the detector. These challenges make the analysis of single molecule trajectories, from pixelated images, a complex problem. Here, we investigate the effect of pixelation on the parameter estimation of single molecule trajectories. In particular, we develop a stochastic framework to calculate the maximum likelihood estimates of the parameters of a stochastic differential equation that describes the motion of the molecule in living cells. We also calculate the Fisher information matrix for this parameter estimation problem. The analytical results are complicated through the fact that the observation process in a microscope prohibits the use of standard Kalman filter type approaches. The analytical framework presented here is illustrated with examples of low photon count scenarios for which we rely on Monte Carlo methods to compute the associated probability distributions.

Different Medical Image Registration Techniques: A Comparative Analysis

Background:

Image registration provides major role in real world applications and classic digital image processing. Image registration is carried out for more than one image and this image was captured from a different location, different sensors, different time and different viewpoints.

Discussion:

This paper deals with the comparative analysis of various registration techniques and here six registration techniques depending upon intensity, phase correlation, image feature, area, control points and mutual information are compared. Comparative analysis for different methodologies shows the advantages of one method over the other methods. The foremost objective of this paper is to deliver a complete reference source for the scholars interested in registration, irrespective of specific application extents.

Conclusion:

Finally performance analyses are evaluated for the medical datasets and comparison is graphically shown with the MATLAB simulation tool.

Orthogonal Probing of Single-Molecule Heterogeneity by Correlative Fluorescence and Force Microscopy

Correlative imaging by fluorescence and force microscopy is an emerging technology to acquire orthogonal information at the nanoscale. Whereas atomic force microscopy excels at resolving the envelope structure of nanoscale specimens, fluorescence microscopy can detect specific molecular labels, which enables the unambiguous recognition of molecules in a complex assembly. Whereas correlative imaging at the micrometer scale has been established, it remains challenging to push the technology to the single-molecule level. Here, we used an integrated setup to systematically evaluate the factors that influence the quality of correlative fluorescence and force microscopy. Optimized data processing to ensure accurate drift correction and high localization precision results in image registration accuracies of ∼25 nm on organic fluorophores, which represents a 2-fold improvement over the state of the art in correlative fluorescence and force microscopy. Furthermore, we could extend the Atto532 fluorophore bleaching time ∼2-fold, by chemical modification of the supporting mica surface. In turn, this enables probing the composition of macromolecular complexes by stepwise photobleaching with high confidence. We demonstrate the performance of our method by resolving the stoichiometry of molecular subpopulations in a heterogeneous EcoRV-DNA nucleoprotein ensemble.

Correlative Atomic Force and Single-Molecule Fluorescence Microscopy of Nucleoprotein Complexes

Correlative imaging by fluorescence and atomic force microscopy provides a versatile tool to extract orthogonal information on structurally heterogeneous biomolecular assemblies. In this chapter, we describe an integrated setup for correlative fluorescence and force microscopy. We present factors influencing data quality, as well as step-by-step protocols for sample preparation, data acquisition, and data processing that yield nanoscale topographic resolution, high image registration accuracy, and single-fluorophore sensitivity. We demonstrate the capabilities of the approach through simultaneous characterization of mesoscale geometry and composition in a multipart nucleoprotein complex.