In the biomedical domain, many terms are neoclassical compounds (composed of several Greek or Latin roots). The study of their morphology is important for numerous applications since it makes it possible to structure, translate, retrieve them efficiently... In this paper, we propose an original yet fruitful approach to carry out this morphological analysis by relying on Japanese, more precisely on terms written in kanjis, as a pivot language. In order to do so, we have developed a specially crafted alignment algorithm relying on analogy learning. Aligning terms with their kanji-based counterparts provides at the same time a decomposition of the term into morphs, and a kanji label for each morph. Evaluated on a dataset of French terms, our approach yields a precision greater than 70% and shows its relevance compared with existing techniques. We also illustrate the interest of this approach through two direct applications of the produced alignments: translating unknown terms and discovering relationships between morphs for terminological structuring.