Biomedical imaging ontologies: A survey and proposal for future work

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Abstract
Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical defi nitions thereby also supporting reasoning over the tagged data. Aim: This paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. The ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data.
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Archival date: 2015-11-21
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References found in this work BETA
Building Ontologies with Basic Formal Ontology.Arp, Robert; Smith, Barry & Spear, Andrew D.
The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration.Smith, Barry; Ashburner, Michael; Rosse, Cornelius; Bard, Jonathan; Bug, William; Ceusters, Werner; Goldberg, Louis J.; Eilbeck, Karen; Ireland, Amelia; Mungall, Christopher J.; Leontis, Neocles & Others,
MIREOT: The Minimum Information to Reference an External Ontology Term.Courtot, Mélanie; Gibson, Frank; Lister, Allyson L.; Malone, James; Schober, Daniel; Brinkman, Ryan R. & Ruttenberg, Alan
Promoting Coherent Minimum Reporting Guidelines for Biological and Biomedical Investigations: The MIBBI Project.Taylor, Chris F.; Field, Dawn; Sansone, Susanna-Assunta; Aerts, Jan; Apweiler, Rolf; Ashburner, Michael; Ball, Catherine A.; Binz, Pierre-Alain; Bogue, Molly; Booth, Tim; Brazma, Alvis; Brinkman, Ryan R.; Michael Clark, Adam; Deutsch, Eric W.; Fiehn, Oliver; Fostel, Jennifer; Ghazal, Peter; Gibson, Frank; Gray, Tanya; Grimes, Graeme; Hancock, John M.; Hardy, Nigel W.; Hermjakob, Henning; Julian, Randall K.; Kane, Matthew; Kettner, Carsten; Kinsinger, Christopher; Kolker, Eugene; Kuiper, Martin; Novere, Nicolas Le; Leebens-Mack, Jim; Lewis, Suzanna E.; Lord, Phillip; Mallon, Ann-Marie; Marthandan, Nishanth; Masuya, Hiroshi; McNally, Ruth; Mehrle, Alexander; Morrison, Norman; Orchard, Sandra; Quackenbush, John; Reecy, James M.; Robertson, Donald G.; Rocca-Serra, Philippe; Rodriguez, Henry; Rosenfelder, Heiko; Santoyo-Lopez, Javier; Scheuermann, Richard H.; Schober, Daniel; Smith, Barry & Snape, Jason
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Citations of this work BETA
Developing the Quantitative Histopathology Image Ontology : A Case Study Using the Hot Spot Detection Problem.Gurcan, Metin; N., Tomaszewski; John, Overton; James, A.; Doyle, Scott; Ruttenberg, Alan & Smith, Barry

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