Texture-based detection of myositis in ultrasonographies

Abstract

Muscle ultrasonography is a convenient technique to visualize healthy and pathological muscle tissue as it is non-invasive and image acquisition can be done in real-time. In this paper, a texture-based approach is presented to detect myositis in ultrasound images automatically. We compute different texture features like wavelet transform features and first-order grey-level intensity statistics of a relevant central image patch carrying structure and intensity information of muscle tissue. Using a combination of these information we reached an accuracy of classification of 92.20% with our approach on a training data set of 63 clinically pre-classified data sets.