One of the most challenging shoulder injuries is rotator cuff tear that increases with aging and particularly happens among athletes. These tears cause pain and highly affect the functionality of the shoulder. The motivation of this work is detecting these tears by microwave tomographic imaging. This imaging method requires the solution of an inverse problem based on a minimization algorithm, with successive solutions of a direct problem. We make use of parallel computation from the domain decomposition method and domain-specific language with the opensource FreeFEM solver. Results demonstrate the possibility to detect tendon tear in a simplified shoulder model.