<title>Quality of DICOM header information for image categorization</title>

Abstract

The widely used DICOM 3.0 imaging protocol specifies optional tags to store specific information on modality and body region within the header: Body Part Examined and Anatomic Structure. We investigate whether this information can be used for the automated categorization of medical images, as this is an important first step for medical image retrieval. Our survey examines the headers generated by four digital image modalities (2 CTs, 2 MRIs) in clinical routine at the Aachen University Hospital within a period of four months. The manufacturing dates of the modalities range from 1995 to 1999, with software revisions from 1999 and 2000. Only one modality sets the DICOM tag Body Part Examined. 90 out of 580 images (15.5%) contained false tag entries causing a wrong categorization. This result was verified during a second evaluation period of one month one year later (562 images, 15.3% error rate). The main reason is the dependency of the tag on the examination protocol of the mOdality, which controls all relevant parameters of the imaging process. In routine, the clinical personnel often applies an examination protocol outside its normal context to improve the imaging quality. This is, however, done without manually adjusting the categorization specific tag values. The values specified by DICOM for the tag Body Part Examined are insufficient to encode the anatomic region precisely. Thus, an automated categorization relying on DICOM tags alone is impossible.

Discriminative cue integration for medical image annotation

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Immediate Structured Visual Search for Medical Images

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A graph-based approach for the retrieval of multi-modality medical images

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