Proximal femur segmentation in conventional pelvic x ray.
A solid and accurate proximal femur segmentation technique using the popular active shape model (ASM) is proposed. For generating an optimal shape prior, the minimum description length, based on 200 supervised manual segmented proximal femur shapes, is used. The segmentation is based on a coarse to fine scaling technique including a profile scale space method. The segmentation results are compared using an optimal defined initial pose and a pose based on a registration technique. Using ideal template initialization, 95% of the shapes have been recovered exactly (average point-to-point error approximately 13 pixels, average point-to-boundary error approximately 7 pixels). Using a template-based initialization based on a registration technique, a successful segmentation rate of approximately 89% is achieved, with an average point-to-point error approximately 12 pixels, and an average point-to-boundary error approximately 8 pixels. With an adequate template initialization and an improved ASM, this method seems to provide an accurate tool for segmentation of the proximal femur shapes on conventional hip overview x-ray images.
Pilgram
Roland
R
Institute of Applied Systems Research & Development, University for Health Sciences, Medical Informatics and Technology (UMIT), 6060 Hall in Tyrol, Austria. roland.pilgram@umit.at
Walch
Claudia
C
Kuhn
Volker
V
Schubert
Rainer
R
Staudinger
Roland
R
D005269:Femur / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010388:Pelvis / Q000000981:diagnostic imaging*; D011859:Radiography; D012680:Sensitivity and Specificity