Project Overview

ILUMINATE (Innovative Lung Cancer Mouse Models recapitulating human immune response and Tumor-Stroma Exchange) develops a novel platform for integrated analysis of in-vivo models for preclinical evaluation of new compounds in oncology, including innovative therapeutic approaches in oncoimmunology. The goal is to provide innovative service models that cover the entire range of in-vivo research, including planning of the study experimental set up, data analysis, and comprehensive visual presentation of results. This approach will meet the expected strong demand from oncology and oncoimmunology research and supports the public interest in efficient and transparent development of novel cancer therapies.

Relevant aspects of the human tumor microenvironment will be reconstructed by co-cultivation of human fibroblasts, immune cells, and tumor cells in immunocompromised mice, to study effects of innovative immunomodulatory therapeutic interventions. The platform comprehensively captures different cell types, labeled by multiplexed immunohistochemistry, in their spatial context. The subsequent modular analysis-workflow integrates elements of multispectral and advanced image analysis. Thus, the evaluation of new compounds reaches far beyond determining simply tumor growth rates, and provides customized approaches for individual new compounds. By developing new analysis methods, ILUMINATE facilitates discovery and evaluation of new compound classes in the development of cancer drugs.

Project Homepage:

ILUMINATE Annotation Viewer

I maintain the Annotation Viewer software used for analysing classification results (unpublished as of now). The software provides a convenient web interface for accessing the quality of automated annotations generated by our dense segmentation network. Drawing

It also provides tools to annotate new whole slide images partly by hand and supporting the network in the process of accurate labeling.


The ILUMINATE Annotation Viewer was build using openslide-python for the backend and OpenSeadragon for efficient rendering of image and annotation. The project will be available on Github soon.