  Medical image fusion is the process of registering and combining multiple
images from single or multiple imaging modalities to improve the imaging
quality and reduce randomness and redundancy in order to increase the clinical
applicability of medical images for diagnosis and assessment of medical
problems. Multi-modal medical image fusion algorithms and devices have shown
notable achievements in improving clinical accuracy of decisions based on
medical images. This review article provides a factual listing of methods and
summarizes the broad scientific challenges faced in the field of medical image
fusion. We characterize the medical image fusion research based on (1) the
widely used image fusion methods, (2) imaging modalities, and (3) imaging of
organs that are under study. This review concludes that even though there
exists several open ended technological and scientific challenges, the fusion
of medical images has proved to be useful for advancing the clinical
reliability of using medical imaging for medical diagnostics and analysis, and
is a scientific discipline that has the potential to significantly grow in the
coming years.
