The field of Medical image processing is one of the widely used and rapidly growing areas of research. It is widely used to diagnose diseases in the medical field. It will be useful to treat the patient better. Soft computing techniques draw the attention of researchers because of their flexibility to work with ownership functions. They are very adaptive in nature, and hence they are the most preferred by researchers and developers. Their advantages are tolerance towards imprecision, approximation, and uncertainty. AI deals with exhibiting human intelligence on machines. Machine learning helps to achieve artificial intelligence. Deep learning helps to implement the machine learning. Goal of this research is to understand various research done in medical image processing domain. We focused primarily on the application of the classification as well as the segmentation methods in the field of medical imaging. With technology growth in the field of medical science along with the growth of soft computing techniques, researchers have carried out various experiments in recent years and published their significant research findings. It is proposed to use a brain image data, retinal image data set and Computer Tomography images for the experiment. The experiment results will be analyzed with respect to some performance measures to make them more suitable for medical analysis, predictions, and other applications.