Paper
3 March 2007 Shape based segmentation of MRIs of the bones in the knee using phase and intensity information
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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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jurgen Fripp, Pierrick Bourgeat, Stuart Crozier, and Sébastien Ourselin "Shape based segmentation of MRIs of the bones in the knee using phase and intensity information", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651212 (3 March 2007); https://doi.org/10.1117/12.711234
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Bone

Magnetic resonance imaging

3D modeling

Tissues

Image filtering

Feature extraction

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