Abstract
Cryo-electron tomography (cryo-ET) is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures. However, cryo-ET imaging has two serious disadvantages—low dose and low image contrast—which result in high-resolution information being obscured by noise and image quality being degraded, and this causes errors in biological interpretation. The purpose of this research is to explore an optimal wavelet denoising technique to reduce noise in cryo-ET images. We perform tests using simulation data and design a filter using the optimum selected wavelet parameters (three-level decomposition, level-1 zeroed out, subband-dependent threshold, a soft-thresholding and spline-based discrete dyadic wavelet transform (DDWT)), which we call a modified wavelet shrinkage filter; this filter is suitable for noisy cryo-ET data. When testing using real cryo-ET experiment data, higher quality images and more accurate measures of a biological structure can be obtained with the modified wavelet shrinkage filter processing compared with conventional processing. Because the proposed method provides an inherent advantage when dealing with cryo-ET images, it can therefore extend the current state-of-the-art technology in assisting all aspects of cryo-ET studies: visualization, reconstruction, structural analysis, and interpretation.
Highlights
Cryo-electron tomography is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures
For cross-scale regularization (CSR) (“w4”), when decomposition level (1, 2) was modified, better performance was achieved than when only modifying decomposition level 1, the results were slightly worse than the best results shown in “w2” and “w3”
The results show that wavelet filters have the potential to improve both the high-resolution information and contrast of cryo-tomograms
Summary
Cryo-electron tomography (cryo-ET) is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures. When testing using real cryo-ET experiment data, higher quality images and more accurate measures of a biological structure can be obtained with the modified wavelet shrinkage filter processing compared with conventional processing. The main purpose of this study is to explore an optimal wavelet transform (WT) method to reduce noise in a cryo-ET image. We describe our proposed method for obtaining optimal wavelet parameters based on our four types of designed wavelet filters, and we present their tested performance capabilities based on simulation data. We compare a wavelet filter designed using optimal parameters against undenoised results based on cryo-ET experiment data.
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