Title :
Intelligent feature selection for model-based bone segmentation in digital radiographs
Author :
Goossen, A. ; Peters, Dirk ; Gernoth, T. ; Pralow, Thomas ; Grigat, Rolf-Rainer
Author_Institution :
Vision Syst. Dept., Hamburg Univ. of Technol., Hamburg, Germany
Abstract :
In this paper we propose a method to enhance Active Shape Model based bone segmentation. One major weakness of the classic algorithm is the use of a single dedicated image feature. However to model the variation of image content along the object boundaries it is more suitable to use different features for different regions. We derive an automatic intelligent selection of these features and integrate it into the classic Active Shape Model segmentation. We evaluated the proposed algorithm on the task of delineating bone structures in more than 150 clinical radiographs of the lower extremity and achieve superior accuracy compared to previously published approaches.
Keywords :
bone; diagnostic radiography; feature extraction; image segmentation; medical image processing; Active Shape Model; digital radiograph; image feature; intelligent feature selection; model based bone segmentation; Active shape model; Biomedical measurements; Bones; Extremities; Image segmentation; Information technology; Orthopedic surgery; Principal component analysis; Radiography; Shafts; Active Shape Models; Bone Structure; Digital Radiography; Orthopedic Measurement; Segmentation;
Conference_Titel :
Information Technology and Applications in Biomedicine, 2009. ITAB 2009. 9th International Conference on
Conference_Location :
Larnaca
Print_ISBN :
978-1-4244-5379-5
Electronic_ISBN :
978-1-4244-5379-5
DOI :
10.1109/ITAB.2009.5394325