A customizable similarity measure between histological cases.

Abstract

IDEM, a computerized environment dedicated to pathologists, includes a Case Based Reasoning (CBR) procedure to retrieve similar histological cases in the database. The relevancy of a retrieved case strongly depends on the similarity measure comparing case descriptions. The present work deals with the definition of a similarity measure in the context of IDEM. In a first step, a theoretical measure (relational, numerical and informed), based on the domain constraints, was selected. In a second step, the theoretical measure is optimized according to the current case base. Results are presented for a database of 53 cases of breast tumors. The contribution of this work is to give to pathologists an interactive environment that optimizes the similarity measure between histological cases. This work is also a contribution to the CBR cycle life since the similarity measure can be adapted while new cases are added to the base.