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Visible Human, Know Thyself:
The Digital Anatomist Structural Abstraction

Cornelius Rosse, M.D., D.Sc., Jose L. V. Mejino, M.D., Linda G. Shapiro, Ph.D., James F. Brinkley, M.D., Ph.D.

Structural Informatics Group, Department of Biological Structure and Computer Science,
University of Washington, Seattle, WA
rosse@u.washington.edu

Abstract
      The Visible Human data sets have stimulated a great deal of activity in the graphical representation of anatomy. A major challenge is to enhance this resource of image-based information with knowledge of its own structure. There is a need for a symbolic model of the structural organization of the human body, which could invest with meaning the graphical information extractable from the clusters of voxels and their geometric coordinates that make up the Visible Human data sets. The objective of this communication is to examine the elements of structural information such a symbolic model should encompass, and to assess the extent to which the Anatomical Structural Abstraction (ASA) of the Digital Anatomist Foundational Model of Anatomy (Fm) meets this objective.
 
Keywords: Anatomical terminology, foundation model, ontology, symbolic model
 
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