Cancer is a deadly disease. It is crucial to diagnose cancer in its early stages. This can be done with medical imaging. Medical imaging helps us scan and view internal organs. The analysis of these images is a very important task in the identification and classification of cancer. Over the past years, the occurrence of cancer has been increasing, so has been the load on the medical fraternity. Fortunately, with the growth of Artificial Intelligence in the past decade, many tools and techniques have emerged which may help doctors in the analysis of medical images. This is a systematic study covering various tools and techniques used for medical image analysis in the field of cancer detection. It focuses on machine learning and deep learning technologies, their performances, and their shortcomings. Also, the various types of imaging techniques and the different datasets used have been discussed extensively. This work also discusses the various preprocessing techniques that have been performed on medical images for better classification. A total of 270 studies from 5 different publications and 5 different conferences have been included and compared on the above-cited parameters. Recommendations for future work have been given towards the end.