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Proceedings Paper

Multiscale salient point-based retrieval of fracture cases
Author(s): Xin Zhou; Richard Stern; Adrien Depeursinge; Henning Müller
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Paper Abstract

Fractures are common injuries, some complicated fractures may require a surgical intervention. When such an operation is planned it can be beneficial to have access to similar past cases including follow ups to compare, which method might be the most adapted one in a particular situation. At the orthopaedic service of the University hospitals of Geneva a database of past cases including pre- and post-operative images and case descriptions has been created over the past years with the goal to support clinical decision making. Images play an important role in the decision making process and the judgment of a fracture, but visual image content is currently not directly accessible for search. At the moment, search is mainly via a classification system of the fractures or in the patient record itself only by patient ID. In this paper we propose a solution that combines visual information from several images in a case to calculate similarity between cases and allow thus an access to visually similar cases. Such a system can complement the text- or classification-based search that has been used so far. In a preliminary study, we used pixel-grid-based salient-point features to build a first prototype of case-based visual retrieval of fracture cases. Cases belonging to different fracture classes were beforehand often confused due to the similar bone structures in the various images. In this article, a multi-scale approach is used in order to perform similarity measures at both large and small scales. When compared to the first prototype, the introduction of scale and spatial information allowed improving the performance of the system. Cases containing similar bone structures but with dissimilar fractures are generally ranked lower whereas more relevant cases are returned. The system can thus be expected to perform sufficiently well for use in clinical practice and particularly for teaching.

Paper Details

Date Published: 25 March 2011
PDF: 13 pages
Proc. SPIE 7967, Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 796706 (25 March 2011); doi: 10.1117/12.878046
Show Author Affiliations
Xin Zhou, Univ. Hospitals of Geneva (Switzerland)
Univ. of Geneva (Switzerland)
Richard Stern, Univ. Hospitals of Geneva (Switzerland)
Adrien Depeursinge, Univ. Hospitals of Geneva (Switzerland)
Univ. of Geneva (Switzerland)
Univ. of Applied Sciences Western Switzerland (Switzerland)
Henning Müller, Univ. Hospitals of Geneva (Switzerland)
Univ. of Geneva (Switzerland)
Univ. of Applied Sciences Western Switzerland (Switzerland)


Published in SPIE Proceedings Vol. 7967:
Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications
William W. Boonn; Brent J. Liu, Editor(s)

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