Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

G.Simko, G. Orban, P. Maday, G. Horvath
Elimination of clavicle shadows to help automatic lung nodule detection on chest radiographs
4th European Conference of the International Federation for Medical and Biological Engineering. Springer Berlin Heidelberg, 2009. (bib)

Lung nodule detection is one of the most important goals of large scale screening of chest radiographs. The success of nodule detection can be increased if it is possible to suppress the bony structures from the chest radiographs. While one possible way to do this is to use dual-energy imaging, most of the commercial X-ray machines do not offer this technology. Finding an alternative approach is an important task. This paper proposes a new solution for it, where first the contours of bones -especially the contours of clavicles- are detected then the shadow of the bones is removed. The performance of the clavicle suppression algorithm is then evaluated by the use of a nodule detection system. The algorithms were tested on images from the JSRT database. The nodule detection algorithm was looking for up to 20 suspicious areas in the original images. According to our first results in the images with suppressed clavicle shadows 20 of 380 false positives were removed, while all true positives were preserved. 69 of the original 380 false positives were around the clavicle, which would mean 24% decrease in the concerned region.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif