A novel registration method based on coevolutionary strategy
Jun Zhang, Jinglu Hu · 2016
Automatic registration is an important task to prepare aligned 2D images for 3D structure visualization, and it is a challenging problem especially for the microscope images. This paper proposes a novel coevolution-based coarse-to-fine registration method, aiming to align the regions of interest (ROIs) in the image sequence. Firstly, a coarse registration for whole images is executed by a scale-invariant feature transform (SIFT) based method, which can facilitate the segmentation of ROIs. Secondly, a fine registration for the segmented ROIs is done by a genetic algorithm (GA) with a novel coevolutionary strategy. Experimental results demonstrate the good performance of the proposed method and it is also successfully applied to the renal biopsy image sequence.