Technique for the computation of lower leg muscle bulk from magnetic resonance images

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.