Abstract
In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset.
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Notes
In this work, we use displayable and geometric models interchangeably.
The gene expression data is however stored in an online server and it is not clear to the authors how this information can be obtained in a machine readable file for integrating with the faceted visualizer. Our discussion is therefore limited to the anatomical structures alone.
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Acknowledgments
This work was supported in part by the NIH NCRR NAC P41-RR13218 and is part of the National Alliance for Medical Image Computing (NAMIC) funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. The authors also thank the reviewers whos’ comments and suggestions greatly helped to improve the manuscript.
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The authors declare that they have no conflict of interest.
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Veeraraghavan, H., Miller, J.V. Faceted Visualization of Three Dimensional Neuroanatomy By Combining Ontology with Faceted Search. Neuroinform 12, 245–259 (2014). https://doi.org/10.1007/s12021-013-9202-5
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DOI: https://doi.org/10.1007/s12021-013-9202-5