Cardiac ischemic injuries can be classified into two main categories: reversible and irreversible. Treatment of reversible damages is possible through revascularization therapies. Clinically, it is quite vital to determine the reversibility of ischemic injuries and local efficiency using accurate diagnostics techniques. For this purpose, a number of imaging techniques have been developed. To our knowledge, while some of these techniques are capable of assessing tissue viability which is believed to be correlated with ischemic injuries reversibility, none of them are capable of providing information about local myocardial tissue efficiency. Note that this efficiency indicates the local tissue contribution to the overall (global) heart mechanical function which is characterized by parameters such as ejection fraction. While contraction force generation of the myocardium is a reliable and straightforward mechanical measure for the local myocardium functionality, it is also hypothesized that the level of damage reversibility expected from therapy is proportional to the intensity and distribution of these forces. As such this research involves developing a new imaging technique for cardiac contraction force quantification. This work is also geared towards another application, namely Cardiac Resynchronization Therapy (CRT), specifically for electrode leads configuration optimization. The latter has not been tackled through a systematic technique thus far. In the proposed method, contraction force reconstruction is accomplished by an inverse problem algorithm solved through an optimization framework which uses forward mechanical modelling of the myocardium iteratively to obtain the contraction forces field. As a result, the method requires a forward mechanical model of the myocardium which is computationally efficient and robust against divergence. Therefore, we developed such a model which considers all aspects of the myocardial mechanics including hyperelasticity, anisotropy, and active contraction forces of the fibers. This model assumes two major parts for the myocardium consisting background tissue and reinforcement bars simulating myocardial fibers. The finite element simulations of this model demonstrated reasonably good performance in mimicking left ventricle (LV) contractile function.