The registration concept is one of the most important and popular aspects of digital image processing. Using suitable computer programming techniques and transformation between two images, a new much more informative image can be found. In this paper, three important and basic medical image registration (MIR) methods, namely MIR by maximization of mutual information, MIR using cross correlation (Fourier transform approach), and MIR by minimization of similarity metric, were proposed and accordingly two comprehensive applications were performed using MIR by minimization of the similarity metric, which uses the sum of the squared differences metric as a metric and the regular step gradient descent optimizer as an optimizer. What is more, MR images of two patients who had brain tumors are registered with different MR images of the same patients at a different time so that growthiness of the tumor inside the patient's brain can be investigated. It is thought that this paper will provide a comprehensive reference source for researchers involved in MIR because this paper contains not only a powerful explanation of three methods of medical image registration but also provides two experimental results using MIR by minimization of the similarity metric.