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DOI: 10.1148/rg.253045071
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Benefits of Content-based Visual Data Access in Radiology1

Henning Müller, PhD, Antoine Rosset, MD, Arnaud Garcia, Jean-Paul Vallée, PhD, MD and Antoine Geissbuhler, MD

1 From the Service of Medical Informatics, University and University Hospitals of Geneva, 24 Rue Michelidu-Crest, 1211 Geneva 14, Switzerland. Presented as an infoRAD exhibit at the 2003 RSNA Scientific Assembly. Received April 12, 2004; revision requested July 1; final revision received January 13, 2005; accepted January 20. All authors have no financial relationships to disclose.


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Figure 1.  Content-based image retrieval as a diagnostic aid with use of medGift and the casimage database. The query image (left) shows emphysematous lesions with multiple confluent centrilobular and paraseptal areas of low attenuation without visible walls. The search results show six images, including five cases of emphysema (right), with each image accompanied by a link to the complete case description. One image demonstrates unilateral emphysema (MacLeod [Swyer-James] syndrome), and two images show a small area of consolidation in the pulmonary parenchyma (cryptogenic organized pneumonia [COP] and pulmonary embolism). The typical pattern of pulmonary parenchyma destruction seen on these five images strongly suggests the diagnosis of emphysema for the query image.

 


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Figure 2.  Partly failed retrieval due to insufficient information in the query image (top left) with respect to varying gray-level changes or strong textures. There is no sharply lined object in the query image, which would have made retrieval easier.

 


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Figure 3.  Extraction of local image features. The image is first partitioned into four equal regions (red lines), and this process is repeated for each successive subregion (blue, green, and yellow lines) to extract local image characteristics.

 


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Figure 4.  Screen shows the interface of medGIFT and casimage. Clicking on an image in the medGIFT interface brings up the corresponding textual case description.

 





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