Fully automatic joint segmentation for computer-aided diagnosis and planning

Publikationstyp
Conference Paper
Date Issued
2010-10-25
Sprache
English
Author(s)
Gooßen, André  
Pralow, Thomas  
Grigat, Rolf-Rainer  
Institut
Bildverarbeitungssysteme E-2  
TORE-URI
http://hdl.handle.net/11420/10032
First published in
Lecture notes in computer science  
Number in series
6357 LNCS
Start Page
132
End Page
139
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6357 LNCS: 132-139 (2010-10-25)
Contribution to Conference
1st International Workshop on Machine Learning in Medical Imaging, 2010  
Publisher DOI
10.1007/978-3-642-15948-0_17
Scopus ID
2-s2.0-77958054822
Publisher
Springer
Orthopaedic examinations are a major reason for radiographic image acquisition. For many diagnostic problems measurements have to be computed from the recorded radiographs. As this task is time-consuming and lacks objectivity, it is desirable to perform these measurements automatically via so-called computational imaging. This requires robust and accurate methods trained and proven on clinical data. We propose a fully automatic technique and present the three complementing stages of our segmentation algorithm. We evaluated the proposed method on more than 200 clinical images and achieve robust and precise delineations, well-suited for automated computation of orthopaedic measurements. © 2010 Springer-Verlag Berlin Heidelberg.
Subjects
Computational Imaging
Cost Path Optimization
Deformable Models
Digital X-Ray
Generalized Hough Transform
Radiography
DDC Class
600: Technik
610: Medizin