Artificial Intelligence in Medicine
Volume 39, Issue 3 , Pages 227-236, March 2007

Comparing two approaches for aligning representations of anatomy

  • Songmao Zhang

      Affiliations

    • Institute of Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, PR China
  • ,
  • Peter Mork

      Affiliations

    • The MITRE Corporation, McLean, VA, USA
  • ,
  • Olivier Bodenreider

      Affiliations

    • U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
    • Corresponding Author InformationCorresponding author. Tel.: +1 301 435 3246; fax: +1 301 480 3035.
  • ,
  • Philip A. Bernstein

      Affiliations

    • Microsoft Research, Redmond, WA, USA

Received 12 October 2004; received in revised form 10 December 2006; accepted 11 December 2006.

Summary 

Objective

To analyze the comparison, through their results, of two distinct approaches applied to aligning two representations of anatomy.

Materials

Both approaches use a combination of lexical and structural techniques. In addition, the first approach takes advantage of domain knowledge, while the second approach treats alignment as a special case of schema matching. The same versions of FMA and GALEN were aligned by each approach. Two thousand one hundred and ninety-nine concept matches were obtained by both approaches.

Methods and results

For matches identified by one approach only (337 and 336, respectively), we analyzed the reasons that caused the other approach to fail.

Conclusions

The first approach could be improved by addressing partial lexical matches and identifying matches based solely on structural similarity. The second approach may be improved by taking into account synonyms in FMA and identifying semantic mismatches. However, only 33% of the possible one-to-one matches among anatomical concepts were identified by the two approaches together. New directions need to be explored in order to handle more complex matches.

Keywords: Ontology, Anatomy, Foundational Model of Anatomy (FMA), GALEN, Ontology alignment

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PII: S0933-3657(06)00189-8

doi:10.1016/j.artmed.2006.12.002

Artificial Intelligence in Medicine
Volume 39, Issue 3 , Pages 227-236, March 2007