MRI Knee Image Enhancement using Image Processing

In the biomedical field, magnetic resonance imaging (MRI) is a process widely used to produce images of internal parts of various parts of the body. One common part of the body that is no stranger to this process is the knee. Despite the clear images that it produces, it is still vulnerable to defects known as technical artifacts. Among the various types of technical artifacts, motion artifacts are one of the many common defects encountered in MRI images. The presence of such defects in knee MRI images could lead to errors in diagnosing and treating a patient’s knee in case that it is injured. This could result into the worsening of the condition of the patient’s knee which would cost them even more. In this research, an image enhancement program was developed that could minimize the effects of technical artifacts, particularly motion artifacts, on knee MRI images. This utilized computer vision techniques like grayscale conversion, edge detection, and morphological transformation. MRI knee images containing motion artifacts were used as input. For the output of the program, it was the enhanced versions of the images displayed against their corresponding original versions. Moreover, Python was the platform used in developing the program.