Study on nonlinear spatial stitching method of SICM images based on adaptive region candidates

Scanning Ion Conductance Microscopy (SICM) can realize three-dimensional, non-invasive imaging of living biological cells, and has made significant progress in fields such as cell biology and medicine. However, constrained by the maximum motion range of the piezoelectric actuator (e.g., 100 μm × 100 μm), it always makes high-precision large-scale scanning technically challenging. In order to address this problem, this study proposes a non-linear spatial stitching method for SICM images based on adaptive region candidates. The method selects overlapping regions through the proposed region candidate strategy, then performs secondary scanning, and it uses pixel-level fitting to utilize the features of the overlapping regions. The scanned images are stitched together by using a non-linear spatial image stitching method, which can effectively expand the scanning range of SICM. Experimental results have shown that the proposed method can achieve stitching in three-dimensional topography scanning images of static regular patterns and different samples such as living cells. The structural similarity index of scanned image obtained by the proposed method is 0.927 (the highest), higher than the traditional method. The new method enables SICM to achieve the ability of scanning imaging from cell size to large-scale tissue scanning imaging.