Abstract

 Machine learning and deep learning which are the subsets of Artificial intelligence, have numerous uses in medical imaging. Advancements in machine learning and deep learning led to drastic improvements in medical imaging fields like the evaluation of risks, recognition, identification, prediction, and treatment results. The decision-making power of computers based on artificial intelligence has elevated the effectiveness and efficiency of human decisions. Techniques based on machine learning and deep learning are not only effective and efficient but also speedy. In the medical field, the stage of the diagnosed disease is of great importance as the treatment and recovery rates depend on it. So based on the best and fastest decisions given by machine learning and deep learning techniques, medical practitioners can give their services in a better way.

We have given a summary of the methods used in medical imaging based on machine learning and deep learning algorithms with the benefits and pitfalls of these algorithms. These algorithms offer remarkable methods for classification, segmentation, and autonomous decision-making ability for the analysis of medical images.