Hui Zhang1, Junqi Xu1, Xutong Kuang2, Shuai Xu2, Xuchen Yu1, Weibo Chen3, Chengyan Wang2, and He Wang1
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 2Human Phenome Institute, Fudan University, Shanghai, China, 3Philips Healthcare, Shanghai, China
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 2Human Phenome Institute, Fudan University, Shanghai, China, 3Philips Healthcare, Shanghai, China
The proposed deep-learning based high resolution
IVIM method can qualitatively and quantitatively improve the assessment of lacunar infarction patients.
Fig.1 The network architecture of our proposed deep learning-based MSH-EPI reconstruction method.
Fig.
3: Representative diffusion weighted images from a patient with old cerebral lacunar infarction with SSH-EPI, conventional and deep learning-based MSH-EPI reconstructions, T1-weighted and T2-weighted images.