3D geometry-based quantification of colocalizations in three-channel 3D microscopy images of soft tissue tumors

We introduce a new model-based approach for automatic quantification of colocalizations in multi-channel 3D microscopy images. The approach is based on different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geometry of subcellular structures as well as to differentiate between different types of colocalizations. Furthermore, we perform a statistical analysis to assess the significance of the determined colocalizations. We have successfully applied our approach to about 400 three-channel 3D microscopy images of human soft-tissue tumors.