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. 2011;5(Suppl 1):58-72.
doi: 10.2174/1874431101105010058. Epub 2011 Jul 27.

Prototypes for content-based image retrieval in clinical practice

Adrien Depeursinge  1 , Benedikt Fischer, Henning Müller, Thomas M Deserno
Affiliations

Prototypes for content-based image retrieval in clinical practice

Adrien Depeursinge et al. Open Med Inform J. 2011.

Abstract

Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice.We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS, SIIM, RSNA, and IEEE ISBI. From 2009 to 2011, the programs of CADdemo@CARS and the CAD Demonstration Workshop at SPIE Medical Imaging were sought for the key word "retrieval" in the title. The systems identified were analyzed and compared according to the hierarchy of gaps for CBIR systems.In total, 70 software demonstrations were analyzed. 5 systems were identified meeting the criterions. The fields of application are (i) bone age assessment, (ii) bone fractures, (iii) interstitial lung diseases, and (iv) mammography. Bridging the particular gaps of semantics, feature extraction, feature structure, and evaluation have been addressed most frequently.In specific application domains, CBIR technology is available for clinical practice. While system development has mainly focused on bridging content and feature gaps, performance and usability have become increasingly important. The evaluation must be based on a larger set of reference data, and workflow integration must be achieved before CBIR-CAD is really established in clinical practice.

Keywords: Content-based image retrieval; diagnosis aid; medical image retrieval; prototypes..

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Figures

Fig. (1)
Fig. (1)
CBIR approach to bone-age assessment.
Fig. (2)
Fig. (2)
Result display for the query image indicated at the top left.
Fig. (3)
Fig. (3)
A Screen shot of the GUI for visual retrieval of fracture cases.
Fig. (4)
Fig. (4)
A screen shot of the GUI for the 3D categorization of the lung tissue.
Fig. (5)
Fig. (5)
Left: the query interface for clinical parameters. Right: a ranked list of retrieved cases.
Fig. (6)
Fig. (6)
Two examples of a 3D query and retrieved results.
Fig. (7)
Fig. (7)
Left: the query interface allowing for online selection of specific image features to be used for retrieval and result visualization. Right: A detail view of the mass region and its localization in the mammogram.
See this image and copyright information in PMC

References

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