Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used for the detection and assessment of coronary artery disease. While myocardial ischemia may be detected visually from the MR images by trained cardiologists or radiologists, it is likely that semi-quantitative or quantitative analysis of the dynamic images can improve the accuracy of diagnoses. Such analyses have yet to be standardized and can be limited by the availability and capability of existing software. In this work we present a modular Matlab-based software solution that can improve the analysis of DCEMRI cardiac perfusion images. The proposed software, MPI2D (Myocardial Perfusion Imaging 2D), allows for semi-automatic processing of perfusion data to estimate kinetic parameters of myocardial perfusion. MPI2D has been used to analyze rest and adenosine stress data in several dozen human subjects imaged at the University of Utah. The myocardial perfusion estimates obtained using MPI2D are similar to published literature values for four analysis models: 2-compartment modeling, Fermi function modeling, Model-independent analysis, and Patlak plot analysis. One expert observer analyzed perfusion data from four subjects on two different occasions to assess the intra-user variability of MPI2D and found good correlation between perfusion estimates on both occasions (y=1.00x-0.02, r=0.98) indicating excellent reproducibility of analysis.