Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
504051 | Computerized Medical Imaging and Graphics | 2015 | 9 Pages |
Abstract
Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches.This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Alba G. Seco de Herrera, Roger Schaer, Dimitrios Markonis, Henning Müller,