Edge-Guided Dual-Modality Image Reconstruction

To utilize the synergy between computed tomography (CT) and magnetic resonance imaging (MRI) data sets from an object at the same time, an edge-guided dual-modality image reconstruction approach is proposed. The key is to establish a knowledge-based connection between these two data sets for the tight fusion of different imaging modalities. Our scheme consists of four inter-related elements: 1) segmentation; 2) initial guess generation; 3) CT image reconstruction; and 4) MRI image reconstruction. Our experiments show that, aided by the image obtained from one imaging modality, even with highly under-sampled data, we can better reconstruct the image of the other modality. This approach can be potentially useful for a simultaneous CT-MRI system.