Matching Medical Images with Deep Learning Networks: A Survey

Abstract

Many patients' lives are being saved by image-guided interventions, and the image registration issue must be regarded as the most difficult and complex problem to solve. However, the latest enormous advancements in machine learning (ML), which include the potential to deploy deep neural networks (DNNs) on modern many-core GPUs, have created a promising opportunity for tackling a variety of medical applications, including registration. The most recent research on medical image registration with DNNs is reviewed in detail in the presented work. All of the relevant papers that have already been published in the subject are included in the systematic review. This thorough overview includes a detailed discussion as well as survey of important ideas, statistical analysis from many perspectives, novelties and key contributions, confiding challenges, future directions, key-enabling approaches, and prospective trends. For readers who are actively involved in the subject, researching state-of-the-art and hoping to present a contribution to future publications, the presented study offers a deep grasp and insight.