  Objective: This article presents an automatic image processing framework to
extract quantitative high-level information describing the micro-environment of
glomeruli in consecutive whole slide images (WSIs) processed with different
staining modalities of patients with chronic kidney rejection after kidney
transplantation. Methods: This four-step framework consists of: 1) approximate
rigid registration, 2) cell and anatomical structure segmentation 3) fusion of
information from different stainings using a newly developed registration
algorithm 4) feature extraction. Results: Each step of the framework is
validated independently both quantitatively and qualitatively by pathologists.
An illustration of the different types of features that can be extracted is
presented. Conclusion: The proposed generic framework allows for the analysis
of the micro-environment surrounding large structures that can be segmented
(either manually or automatically). It is independent of the segmentation
approach and is therefore applicable to a variety of biomedical research
questions. Significance: Chronic tissue remodelling processes after kidney
transplantation can result in interstitial fibrosis and tubular atrophy (IFTA)
and glomerulosclerosis. This pipeline provides tools to quantitatively analyse,
in the same spatial context, information from different consecutive WSIs and
help researchers understand the complex underlying mechanisms leading to IFTA
and glomerulosclerosis.
