Graph-based Mathematical Morphology for the Characterization of the Spatial Organization of Histological Structures in High-Content Images : Application to Tumor Microenvironement in Breast Cancer

Abstract : One of the most challenging problems in histological image analysis is the evaluation of the spatial organizations of histological structures in the tissue. In fact, histological sections may contain a very large number of cells of different types and irregularly distributed, which makes their spatial content indescribable in a simple manner. Graph-based methods have been widely explored in this direction, as they are effective representation tools having the expressive ability to describe spatial characteristics and neighborhood relationships that are visually interpreted by the pathologist. We can distinguish three main families of graph-based methods used for this purpose: syntactic structure analysis, network analysis and spectral analysis. However, another distinctive set of methods based on mathematical morphology on graphs can be additionally developed for this issue. The main goal of this dissertation is the development of a framework able to provide quantitative evaluation of the spatial arrangements of histological structures using graph-based mathematical morphology.
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Bassem Ben Cheikh. Graph-based Mathematical Morphology for the Characterization of the Spatial Organization of Histological Structures in High-Content Images : Application to Tumor Microenvironement in Breast Cancer. Image Processing [eess.IV]. Université Pierre et Marie Curie - Paris VI, 2017. English. ⟨NNT : 2017PA066286⟩. ⟨tel-02295572⟩

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