Abstract
An unsupervised technique to estimate the relative size of a patient's lower leg musculature in vivo using magnetic resonance imaging (MRI) in the context of venous insufficiency is presented. This post-acquisition technique was designed to segment calf muscle bulk, which could be used to make inter- or intra-patient comparisons of calf muscle size in the context of unilateral leg ulcers and venous return. Pre-processing stages included partial volume reduction, intensity inhomogeneity correction and contrast equalization. The algorithm created a binary mask of voxels that fell within a computed threshold designated as representing muscle based on a 3-class fuzzy clustering approach. The segmentation was improved using a set of morphological operations to remove adipose tissue, spongy bone and cortical bone. The technique was evaluated for accuracy against a manual segmented ground truth. Results showed that the automatic technique performed sufficiently well in terms of accuracy and efficacy. The automatic method did not suffer from intra-observer variability.
Original language | English |
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Pages (from-to) | 926-933 |
Number of pages | 8 |
Journal | Medical Engineering and Physics |
Volume | 32 |
Issue number | 8 |
DOIs | |
Publication status | Published - Oct 2010 |
Externally published | Yes |
Keywords
- Calf muscle bulk
- Image processing
- Magnetic resonance imaging
- Unsupervised segmentation