Multispectral MR images segmentation using SOM network

The precise segmentation of magnetic resonance images (MRI) is an important subject in both medical and computer science communities. With MRI's property of multi-spectrum, we use the information from its PD-,T1-, and T2-weighted images, mapping them into a multi-dimensional intensity space and getting its vector gradient. Through the improvement of the step function, an unsupervised self-organizing map (SOM) neural network is trained dynamically. To improve the effectiveness of segmentation, we develop a semi-supervised training scheme at the edge of image in multi-dimensional intensity space.