Calculation of the modulation transfer function (MTF) is a multi-step procedure. At each step in the calculation, the algorithms can have intrinsic errors which are independent of the imaging system or physics. We designed a software tool with a graphical user interface to facilitate calculation of MTF and the analysis of accuracy in those calculations. To minimize the source of errors, simulated edge images without any noise or artifacts were used. We first examined the accuracy of a commonly used edge-slope estimation algorithm; namely line-by-line differentiation followed by a linear regression fit. The influence of edge length and edge phase on the linear regression algorithm is demonstrated. Furthermore, the relationship of edge-slope estimation error and MTF error are illustrated. We compared the performance of two kernels, [-1,1] and [-1,0,1], in the computation of the line spread function (LSF) from finite element differentiation of the edge spread function (ESF). We found that there is no practical advantage in choosing the [-1,0,1] kernel, as recommended by IEC. However, a correction for finite element differentiation should be applied; otherwise, there is a measurable error in the MTF. Finally, we added noise into the edge images and compared the performance of two noise reduction methods on the ESF; convolution with a boxcar kernel and a monotonicity constraint. The former method always produces MTF error higher than 4% up to the sampling frequency, while the latter was consistently less than 1%.