Sinogram Denoising of Cryo-Electron Microscopy Images
Taneli Mielikäinen and Janne Ravantti
In: ICCSA 2005, 9-12 May 2005, Singapore.
Cryo-electron microscopy has recently been recognized as a useful
alternative to obtain three-dimensional density maps of macromolecular
complexes, especially when crystallography and NMR techniques
fail. The three-dimensional model is constructed from large
collections of cryo-electron microscopy images of identical particles
in random (and unknown) orientations.
The major problem with cryo-electron microscopy is that the images are
very noisy as the signal-to-noise ratio can be below one. Thus,
standard filtering techniques are not directly
applicable. Traditionally, the problem of immense noise in the
cryo-electron microscopy images has been tackled by clustering the
images and computing the class averages. However, then one has to
assume that the particles have only few preferred orientations.
In this paper we propose a sound method for denoising cryo-electron
microscopy images using their Radon transforms. The method assumes
only that the images are from identical particles but nothing is
assumed about the orientations of the particles. Our preliminary
experiments show that the method can be used to improve the image
quality even when the signal-to-noise ratio is very low.