A marker-free automatic alignment method based on scale-invariant features

In electron tomography, alignment accuracy is critical for high-resolution reconstruction. However, the automatic alignment of a tilt series without fiducial markers remains a challenge. Here, we propose a new alignment method based on Scale-Invariant Feature Transform (SIFT) for marker-free alignment. The method covers the detection and localization of interest points (features), feature matching, feature tracking and optimization of projection parameters. The proposed method implements a highly reliable matching strategy and tracking model to detect a huge number of feature tracks. Furthermore, an incremental bundle adjustment method is devised to tolerate noise data and ensure the accurate estimation of projection parameters. Our method was evaluated with a number of experimental data, and the results exhibit an improved alignment accuracy comparable with current fiducial marker alignment and subsequent higher resolution of tomography.