Ontology-driven image analysis for histopathological images

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Abstract

Ontology-based software and image processing engine must cooperate in new fields of computer vision like microscopy acquisition wherein the amount of data, concepts and processing to be handled must be properly controlled. Within our own platform, we need to extract biological objects of interest in huge size and high-content microscopy images. In addition to specific low-level image analysis procedures, we used knowledge formalization tools and high-level reasoning ability of ontology-based software. This methodology made it possible to improve the expressiveness of the clinical models, the usability of the platform for the pathologist and the sensitivity or sensibility of the low-level image analysis algorithms. © 2010 Springer-Verlag.

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Othmani, A., Meziat, C., & Loménie, N. (2010). Ontology-driven image analysis for histopathological images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6453 LNCS, pp. 1–12). https://doi.org/10.1007/978-3-642-17289-2_1

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