Model-based 3D object detection from multivariate confocal microscopy images

The paper addresses the problem of both prior modeling and object labeling in multivariate microscopy imaging. We make use of a statistical, nonparametric framework to formulate the prior knowledge on microscopy imaging and a model validation technique to achieve the object detection and labeling goal. The approach has been applied in investigations of spatial distribution of nuclei within the colonic glands of rats observed with the help of confocal fluorescence microscopy.