FEATURE-BASED REGISTRATION OF CONFOCAL FLUORESCENCE ENDOMICROSCOPY IMAGES

In this paper, we propose a feature-based registration algorithm for the confocal fluorescence images captured by an endomicroscopy system. We first extract a number of feature points from the endomicroscopy images by applying the binarization-thinning process and using the Rutovitz crossing number. These feature points are then post-processed to eliminate the spurious ones. After that we use the purified feature points to complete the image registration between every two consecutive slice images. The aligned image stack will be finally utilized to reconstruct and visualize the 3D structure of the living cell and tissue in real time, which provides the opportunity for the clinicians to diagnose various diseases including the early-stage cancers.