An automatic framework to study the tissue micro-environment of renal glomeruli in differently stained consecutive digital whole slide images - Université Claude Bernard Lyon 1 Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2020

An automatic framework to study the tissue micro-environment of renal glomeruli in differently stained consecutive digital whole slide images

Résumé

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 three step framework consists of: 1) cell and anatomical structure segmentation based on colour decon-volution and deep learning 2) fusion of information from different stainings using a newly developed registration algorithm 3) 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 in-terstitial fibrosis and tubular atrophy (IFTA) and glomeru-losclerosis. 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.
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Dates et versions

hal-02925040 , version 1 (28-08-2020)

Identifiants

  • HAL Id : hal-02925040 , version 1

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Odyssée Merveille, Thomas Lampert, Jessica Schmitz, Germain Forestier, Friedrich Feuerhake, et al.. An automatic framework to study the tissue micro-environment of renal glomeruli in differently stained consecutive digital whole slide images. 2020. ⟨hal-02925040⟩
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