CNN based Super-Resolution of Intravoxel Incoherent Motion Imaging for Liver

We investigated the super-resolution reconstruction method for IVIM imaging based on convolution neural networks (CNN). Three-layers-CNN was constructed and trained rstly with a series of paired low-and high-resolution images, and then the super-resolution IVIM images were reconstructed with such network, the reconstruction quality was evaluated nally in terms of PSNR, SSIM, di usivity, perfusion fraction and pseudo-di usivity respectively. The results show that the CNN-based super resolution reconstruction for IVIM has a great performance and may enable IVIM to be analyzed with unprecedent resolution.