A Review on Cross-modality Synthesis from MRI to PET

Medical Imaging Synthesis is gaining wide popularity with time. Among the distinctive imaging techniques, MRI and PET have marked their significance in the field of medical care. But due to certain limitations of PET such as the expense, radiation exposure and lack of availability, there's an inclination towards the approach of cross-modality synthesis. Deep learning has paved its way for the advancement of models in this domain, accomplishing the cross-modality synthesis task. Synthesizing biomedical images using such models can save time, money, and effort of patients as well as improve disease diagnosis. This paper means to sum up the deep learning models developed with the end goal of MRI-to-PET cross-modality synthesis.