Ontology-driven Image Analysis for Histopathological Images

6533b82efe1ef96bd1293cad

RESEARCH PRODUCT

Ontology-driven Image Analysis for Histopathological Images

Nicolas Loménie Ahlem Othmani Carole Meziat

subject

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing Computer science [INFO.INFO-IM] Computer Science [cs]/Medical Imaging ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing Ontology (information science)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imaging 03 medical and health sciences [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0302 clinical medicine Software [STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Digital image processing [ INFO.INFO-TI ] Computer Science [cs]/Image Processing [INFO.INFO-IM]Computer Science [cs]/Medical Imaging Computer vision RDF Image analysis [STAT.AP]Statistics [stat]/Applications [stat.AP]Information retrieval [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging business.industry [ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Usability computer.file_format Automatic image annotation [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]030220 oncology & carcinogenesis [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Artificial intelligence business computer

description

International audience; 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.

year	journal	country	edition	language
2010-11-29

https://hal.archives-ouvertes.fr/hal-00646394/file/OTHMANI_ISVC_2010.pdf

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