Unsupervised Segmentation of MRI using Independent Component Analysis
Nalan Özkurt, Ahmet Özkurt · 2007
In this study, an autonomous classification and segmentation algorithm to diagnose and trace multiple sclerosis (MS), from magnetic resonance (MR) imaging is developed. In this method, new image stacks are derived by using three different weighted MR images, and then, independent components are obtained from those images derived. A decision maker is developed in order to choose the most suitable independent component by using spatial tone and MRI tissue properties.