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Medical case retrieval from a committee of decision trees.

Research paper by Gwénolé G Quellec, Mathieu M Lamard, Lynda L Bekri, Guy G Cazuguel, Christian C Roux, Béatrice B Cochener

Indexed on: 04 Sep '10Published on: 04 Sep '10Published in: IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society



Abstract

A novel content-based information retrieval framework, designed to cover several medical applications, is presented in this paper. The presented framework allows the retrieval of possibly incomplete medical cases consisting of several images together with semantic information. It relies on a committee of decision trees, decision support tools well suited to process this type of information. In our proposed framework, images are characterized by their digital content. It was applied to two heterogeneous medical datasets for computer-aided diagnoses: a diabetic retinopathy follow-up dataset (DRD) and a mammography-screening dataset (DDSM). Measure of precision among the top five retrieved results of 0.788 + or - 0.137 and 0.869 + or - 0.161 was obtained on DRD and DDSM, respectively. On DRD, for instance, it increases by half the retrieval of single images.