Abstract
Confocal laser scanning microscope (CLSM) is a powerful tool for studying biological specimens three-dimensionally. Compared with other microscopes, CLSM can provide images with higher resolution and better contrast. However, the resolution along the Z-axis (the optical axis) is much lower than that along the lateral directions. This phenomenon may hamper the spatial reliability of the reconstructed three dimensional volume data of the specimen. One way to increase the resolution in the Z-axis direction is Tilted-view Microscopy. By rotating the specimen, image stacks from different observation angles can be acquired with conventional CLSM. Missing information that can't be recorded from a single direction, due to the poor Z-axial resolution, can be recorded from other directions. Images derived from different observation angles are then combined to reconstruct one volume data with equal lateral and axial resolutions. We propose an image fusion algorithm for the multi-angle image stacks derived by Tilted-view Microscopy to reconstruct a 3D volume data of the specimen that has equal lateral and axial resolutions. In this algorithm, image stacks are first deconvoluted with a depth-variant deconvolution method to recover the distortions caused by point spread functions. Then, deconvoluted image stacks are integrated through a feature-based registration algorithm. Finally, an intensity-based interpolation is applied to predict the absent information that is not recorded by these multi-angle images. As a result, a 3D volume data of the specimen with equal lateral and axial resolutions, which has the real points from multi-angle images and the predicted points that are not recorded by these images, is reconstructed.