An overview of multi-modal medical image fusion

Multi-modal medical image fusion is the process of merging multiple images from single or multiple imaging modalities to improve the imaging quality with preserving the specific features. Medical image fusion covers a broad number of hot topic areas, including image processing, computer vision, pattern recognition, machine learning and artificial intelligence. And medical image fusion has been widely used in clinical for physicians to comprehend the lesion by the fusion of different modalities medical images. In this review, methods in the field of medical image fusion are characterized by (1) image decomposition and image reconstruction, (2) image fusion rules, (3) image quality assessments, and (4) experiments on the benchmark dataset. In addition, this review provides a factual listing of scientific challenges faced in the field of multi-modal medical image fusion.