Automated algorithm to delineate Z-bands in electron microscopic images of the human skeletal muscle

The effects of exercise, nutrition, and aging on the development of human skeletal muscles can be observed from the morphological changes of the Z-band under the electron microscope. Quantification of the Z-band damage has provided useful information to exercise physiology research but is usually a labor-intensive process. In this study, an automated image-processing algorithm has been developed to delineate the Z-band with a given start point. The algorithm detects the borders of the Z-band in an incremental fashion along the long axis. At each step of the iteration local border points are detected along radial directions and the centerline is extended toward both ends of the Z-band. The process iterates itself until a stopping criterion is met. The algorithm has been coded in C++ and used in our laboratory for exercise science research. The software has significantly reduced the processing time and provided reliable high-quality data for the study of Z-band damage.