Spatial interaction analysis with graph based mathematical morphology for histopathology
| Autor: | Bassem Ben Cheikh, Daniel Racoceanu, Nicolas Elie, Benoît Plancoulaine, Catherine Bor-Angelier |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Tumor microenvironment medicine.medical_specialty Computer science business.industry Spatial interaction Graph based Representation (systemics) Digital pathology Cancer Computational biology Image segmentation Mathematical morphology medicine.disease 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Breast cancer 030220 oncology & carcinogenesis medicine Histopathology Computer vision Artificial intelligence business |
| Zdroj: | ISBI |
| Popis: | Exploring the spatial interactions between tumor and the inflammatory microenvironment using digital pathology image analysis can contribute to a better understanding of the immune function and tumor heterogeneity. We address this by providing tools able to reveal various metrics describing spatial relationships in the cancer ecosystem. The approach comprises nuclei segmentation and classification, using supervised learning algorithm, to detect lymphoid aggregates and tumor patterns, and spatial distribution quantification using sparse sets' mathematical morphology. Tumor patterns were classified into three groups: surrounded by lymphocytes, close to lymphoid aggregates or distant and might be protected from immune attack. The approach provides statistical assessment and comprehensive visual representation of the inflammatory tumor microenvironment. |
| Databáze: | OpenAIRE |
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