Details

Autor(en) / Beteiligte

• S., Saritha
• G., Santhosh Kumar
• Venugopal, K. R.
• Patnaik, L. M.

Titel

Interestingness Analysis of Semantic Association Mining in Medical Images

Ist Teil von

• Computer Networks and Intelligent Computing, p.1-10

Ort / Verlag

Berlin, Heidelberg: Springer Berlin Heidelberg

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Medical images provide rich information and are repositories of implicit knowledge, which can be mined effectively. Diagnosis rules, new and established ones can be revealed and verified from the patterns existing in a medical image. In this paper, the spatial patterns existing in medical images are mined to obtain association rules of the diagnosis rules’ category. The semantics of the association rules obtained are highly improved by introducing the concept of fuzziness into the spatial relationships existing between the anatomical structures. The utility of the association rules extracted is analyzed through the interestingness measures computed, and it is thereby concluded that the rules mined are highly relevant.