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Spatial interaction analysis with graph based mathematical morphology for histopathology | IEEE Conference Publication | IEEE Xplore

Spatial interaction analysis with graph based mathematical morphology for histopathology

Publisher: IEEE

Abstract:

Exploring the spatial interactions between tumor and the inflammatory microenvironment using digital pathology image analysis can contribute to a better understanding of ...View more

Abstract:

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.
Date of Conference: 18-21 April 2017
Date Added to IEEE Xplore: 19 June 2017
ISBN Information:
Electronic ISSN: 1945-8452
Publisher: IEEE
Conference Location: Melbourne, VIC, Australia

References

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