Skip navigation.

UCSD Computer Vision

Automated CTF Estimation

Satya Mallick, David Kriegman


Synopsis

In this paper we present a completely automated algorithm for estimating the parameters of the contrast transfer function (CTF) of a transmission electron microscope. The primary contribution of this paper is the determination of the astigmatism prior to the estimation of the CTF parameters. The CTF parameter estimation is then reduced to a 1D problem using elliptical averaging. We have also implemented an automated method to calculate lower and upper cutoff frequencies to eliminate regions of the power spectrum which perturb the estimation of the CTF parameters. The algorithm is comprised of three optimization subproblems, two of which are proven to be convex. Results of the CTF estimation method are presented for images of carbon support films as well as for images of single particles embedded in ice and suspended over holes in the support film. A MATLAB implementation of the algorithm, called ACE, is freely available.

More info on: http://graphics.ucsd.edu/~spmallick/research/ace/index.html


Non UCSD Vision People also Involved

Bridget Carragher and Clinton S. Potter (TSRI)