Bias and variance reduction and denoising for CTF Estimation
This addresses the need for precise CTF estimation in cryo-electron microscopy to improve image reconstruction for structural biology, though it appears incremental as it builds on existing multi-taper methods.
The paper tackles the problem of estimating the contrast transfer function (CTF) in electron microscopy imaging, which is corrupted by lens distortions, by introducing a novel method based on the multi-taper approach to reduce bias and variance, resulting in accurate capture of CTF zero-crossings in low-mid frequency ranges.
When using an electron microscope for imaging of particles embedded in vitreous ice, the objective lens will inevitably corrupt the projection images. This corruption manifests as a band-pass filter on the micrograph. In addition, it causes the phase of several frequency bands to be flipped and distorts frequency bands. As a precursor to compensating for this distortion, the corrupting point spread function, which is termed the contrast transfer function (CTF) in reciprocal space, must be estimated. In this paper, we will present a novel method for CTF estimation. Our method is based on the multi-taper method for power spectral density estimation, which aims to reduce the bias and variance of the estimator. Furthermore, we use known properties of the CTF and of the background of the power spectrum to increase the accuracy of our estimation. We will show that the resulting estimates capture the zero-crossings of the CTF in the low-mid frequency range.