An image processing approach to analyze morphological features of microscopic images of muscle fibers

• We presented an image processing pipeline that is tailored to model and analyze the two-channel images of muscle fibers.
• The method integrates information from the two-channel to reduce artifacts in the results.
• The method quantifies morphological and geometric features of nuclei and cytoplasm of muscle fibers and derives other measurements about muscle fibers.

We present an image processing approach to automatically analyze duo-channel microscopic images of muscular fiber nuclei and cytoplasm. Nuclei and cytoplasm play a critical role in determining the health and functioning of muscular fibers as changes of nuclei and cytoplasm manifest in many diseases such as muscular dystrophy and hypertrophy. Quantitative evaluation of muscle fiber nuclei and cytoplasm thus is of great importance to researchers in musculoskeletal studies. The proposed computational approach consists of steps of image processing to segment and delineate cytoplasm and identify nuclei in two-channel images. Morphological operations like skeletonization is applied to extract the length of cytoplasm for quantification. We tested the approach on real images and found that it can achieve high accuracy, objectivity, and robustness.