GSCFN: A graph self-construction and fusion network for semi-supervised brain tissue segmentation in MRI

In this paper, we propose a graph self-construction and fusion network (GSCFN) for semi-supervised brain tissue segmentation in Magnetic Resonance Imaging (MRI) by fusing multiple types of image features. Compared to the use of a single feature, various features bring complementary information and can contribute to a better graph representation with a great discriminative power increase. But to do so, two problems need to be solved. The first...