Research on the Modality Transfer Method of Brain Imaging Based on Generative Adversarial Network - Cheng, Dapeng; Qiu, Nuan; Zhao, Feng; Mao, Yanyan; Li, Chengnuo (Frontiers in Neuroscience, 2021)
Brain imaging technology is an important means to study brain diseases. The commanly used brain imaging technologies are fMRI and EEG. Clinical practice has shown that although fMRI is superior to EEG in observing the anatomical details of some diseases that are difficult to diagnose, its costs is prohibitive. In particular, more and more patients who use metal implants cannot use this technology. In contrast, EEG technology is easier to implement. Therefore, in order to break through the limitations of fMRI technology, we propose a brain imaging modality transfer framework, namely BMT-GAN, based on generative adversarial network. The framework introduces a new non-adversarial loss to reduce the perception and style difference between input and output images. It also realizes the conversion from EEG modality data to fMRI modality data, and provides comprehensive reference information of EEG and fMRI for radiologists. Finally, a qualitative and quantitative comparison with the existing GAN-based brain imaging modality transfer approachs demonstrates the superiority of our framework.