A Systematic Literature Review on Multi-modal Medical Image Registration

Abstract

Context: In today’s health care, multi-modal image registration increasingly important role in medical analysis and diagnostics. Multi-modal image registration is a challenging task because of the different imaging conditions that changes from one imaging modality to another. Objective: The purpose of this work is to determine the current state of the art in the field of medical image registration shedding light on techniques that have been used to register medical image combinations from different modalities and the importance of combining different modalities in automatic way in the medical domain. Method: To fulfill this objective we chose a Systematic Literature Review (SLR) as method to follow. Which allows to collect and structure the information that exists in the field of multi-modal image registration. Results: Several automatic solutions based on different registration techniques were proposed according to each specific modality combination. Conclusion: The results provide the following conclusions: First, the machine learning in the recent years plays an important role in the automatic registration process. An important number of research propose a learning-based registration solution. Second, There few solutions in literature that tackle the automatic registration of histology - CT modality combination. Finally, the existing research work propose registration solutions for only combination of two modalities. A very few number of work suggest a tri-modality combining.