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Proceedings Paper

Shape based segmentation of MRIs of the bones in the knee using phase and intensity information
Author(s): Jurgen Fripp; Pierrick Bourgeat; Stuart Crozier; Sébastien Ourselin
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Paper Abstract

The segmentation of the bones from MR images is useful for performing subsequent segmentation and quantitative measurements of cartilage tissue. In this paper, we present a shape based segmentation scheme for the bones that uses texture features derived from the phase and intensity information in the complex MR image. The phase can provide additional information about the tissue interfaces, but due to the phase unwrapping problem, this information is usually discarded. By using a Gabor filter bank on the complex MR image, texture features (including phase) can be extracted without requiring phase unwrapping. These texture features are then analyzed using a support vector machine classifier to obtain probability tissue matches. The segmentation of the bone is fully automatic and performed using a 3D active shape model based approach driven using gradient and texture information. The 3D active shape model is automatically initialized using a robust affine registration. The approach is validated using a database of 18 FLASH MR images that are manually segmented, with an average segmentation overlap (Dice similarity coefficient) of 0.92 compared to 0.9 obtained using the classifier only.

Paper Details

Date Published: 3 March 2007
PDF: 9 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651212 (3 March 2007); doi: 10.1117/12.711234
Show Author Affiliations
Jurgen Fripp, CSIRO ICT Ctr. (Australia)
Univ. of Queensland (Australia)
Pierrick Bourgeat, CSIRO ICT Ctr. (Australia)
Stuart Crozier, Univ. of Queensland (Australia)
Sébastien Ourselin, CSIRO ICT Ctr. (Australia)


Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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