title: Medical case retrieval from a committee of decision trees.
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.
authors.affiliation: INSTITUT TELECOM/TELECOM Bretagne, Dpt ITI, Brest, F-29200 France. gwenole.quellec@telecom-bretagne.eu
authors.forename: Gwénolé
authors.initials: G
authors.lastname: Quellec
authors.forename: Mathieu
authors.initials: M
authors.lastname: Lamard
authors.forename: Lynda
authors.initials: L
authors.lastname: Bekri
authors.forename: Guy
authors.initials: G
authors.lastname: Cazuguel
authors.forename: Christian
authors.initials: C
authors.lastname: Roux
authors.forename: Béatrice
authors.initials: B
authors.lastname: Cochener
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical; D003663:Decision Trees; D003930:Diabetic Retinopathy / Q000175:diagnosis; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005654:Fundus Oculi; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016247:Information Storage and Retrieval / Q000379:methods*; D008327:Mammography; D012815:Signal Processing, Computer-Assisted