Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.

Xie, Weiguo; Franke, Jochen; Chen, Cheng; Grützner, Paul A.; Schumann, Steffen; Nolte, Lutz-Peter; Zheng, Guoyan (2014). Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs. International Journal of Computer Assisted Radiology and Surgery, 9(2), pp. 165-176. Springer 10.1007/s11548-013-0932-5

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PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Xie, Weiguo; Chen, Cheng; Schumann, Steffen; Nolte, Lutz-Peter and Zheng, Guoyan

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

1861-6410

Publisher:

Springer

Language:

English

Submitter:

Guoyan Zheng

Date Deposited:

24 Sep 2014 16:42

Last Modified:

25 Nov 2015 10:48

Publisher DOI:

10.1007/s11548-013-0932-5

PubMed ID:

23900851

BORIS DOI:

10.7892/boris.46480

URI:

https://boris.unibe.ch/id/eprint/46480

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