Accuracy Evaluation for Region Centroid-Based Registration of Fluorescent CLSM Imagery

Abstract

We present an accuracy evaluation of a semiautomatic registration technique for 3D volume reconstruction from fluorescent confocal laser scanning microscope (CLSM) imagery. The presented semiautomatic method is designed based on our observations that (a) an accurate point selection is much harder than an accurate region (segment) selection for a human, (b) a centroid selection of any region is less accurate by a human than by a computer, and (c) registration based on structural shape of a region rather than based on intensity-defined point is more robust to noise and to morphological deformation of features across stacks. We applied the method to image mosaicking and image alignment registration steps and evaluated its performance with 20 human subjects on CLSM images with stained blood vessels. Our experimental evaluation showed significant benefits of automation for 3D volume reconstruction in terms of achieved accuracy, consistency of results, and performance time. In addition, the results indicate that the differences between registration accuracy obtained by experts and by novices disappear with the proposed semiautomatic registration technique while the absolute registration accuracy increases.