Registration of serial transverse sections of muscle fibers

Abstract

Structural and functional characterization of skeletal muscles is often assessed by histochemical techniques, which enable the classification into different fiber types by combining the reactions in serial transverse muscle cross-sections. A drawback is that a knowledgeable operator is required to combine and evaluate the reactions, which is a time-consuming, tedious, and subjective task. To enhance the speed and reproducibility of muscle fiber typing, the registration of serial transverse sections of muscle fibers images has been proposed as a preprocessing step. Three different registration methods were considered: first, a semi-automatic elastic point-based registration; second, an automatic (rigid, affine, and projective) whole image content-based registration; and, third, an automatic hierarchical elastic registration obtained by integration of the first two methods. The performances of the methods were tested on a database of 50 image stacks each containing three images of histochemically differently stained serial human muscle cross-sections. The amounts of successful globally and locally registered stacks were approximately 20% for automatic rigid registration, 60% for automatic affine and projective registrations, and 80% for semi-automatic and automatic elastic registration. By using robust elastic registration methods, the automatic registration of serial transverse muscle fiber images seems feasible and might allow automatic muscle fiber typing, and consequently, improve the characterization of skeletal muscles.