While the public has increasingly access to medical information, specialized medical language is often difficult for non-experts to understand and there is a need to bridge the gap between specialized language and lay language. As a first step towards this end, we describe here a method to build a comparable corpus of expert and non-expert medical French documents and to identify similar text segments of lay and specialized language. Among the top 400 pairs of text segments retrieved with this method, 59% were actually similar and 37% were deemed exploitable for further processing. This is encouraging evidence for the target task of finding equivalent expressions between these two varieties of language.