Paper
30 March 2007 Semi-automated location identification of catheters in digital chest radiographs
Brad M. Keller, Anthony P. Reeves, Matthew D. Cham, Claudia I. Henschke, David F. Yankelevitz
Author Affiliations +
Abstract
Localization of catheter tips is the most common task in intensive care unit imaging. In this work, catheters appearing in digital chest radiographs acquired by portable chest x-rays were tracked using a semi-automatic method. Due to the fact that catheters are synthetic objects, its profile does not vary drastically over its length. Therefore, we use forward looking registration with normalized cross-correlation in order to take advantage of a priori information of the catheter profile. The registration is accomplished with a two-dimensional template representative of the catheter to be tracked generated using two seed points given by the user. To validate catheter tracking with this method, we look at two metrics: accuracy and precision. The algorithms results are compared to a ground truth established by catheter midlines marked by expert radiologists. Using 12 objects of interest comprised of naso-gastric, endo-tracheal tubes, and chest tubes, and PICC and central venous catheters, we find that our algorithm can fully track 75% of the objects of interest, with a average tracking accuracy and precision of 85.0%, 93.6% respectively using the above metrics. Such a technique would be useful for physicians wishing to verify the positioning of catheter tips using chest radiographs.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Brad M. Keller, Anthony P. Reeves, Matthew D. Cham, Claudia I. Henschke, and David F. Yankelevitz "Semi-automated location identification of catheters in digital chest radiographs", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65141O (30 March 2007); https://doi.org/10.1117/12.707769
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CITATIONS
Cited by 11 scholarly publications and 2 patents.
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KEYWORDS
Chest imaging

Detection and tracking algorithms

Radiography

Signal attenuation

Electronic filtering

Image filtering

Chest

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