Some studies suggest fat infiltration in the lumbar muscles (LM) is associated with lower back pain (LBP) in adults. Usually fat in MRI-defined lumbar muscles is qualitatively valuated by visual grading via a 3 point scale, whereas a quantitative continuous (0 - 100%) approach may provide a greater insight. In this paper, we propose a method to precisely quantify the fat content / infiltration in a user-defined region of the lumbar muscles, which may aid better diagnosis. The key steps are segmenting the region of interest (ROI) from the lumbar muscles, identifying the fatty regions in the segmented region based on the selected threshold and softness levels, computing the parameters (such as total and region-wise fat content percentage, total-cross sectional area (TCSA), functional cross- sectional area (FCSA)) and exporting the computations and associated patient information from the MRI, into a atabase. A standalone application using MATLAB R2010a was developed to perform the required computations along with an intuitive GUI.