Esmeralda Ruiz Pujadas1, Martin Buechert1, Michael Weiner2, Stathis Hadjidemetriou1
1Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany; 2Department of Radiology, VA Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, United States
Image segmentation plays an important role in many medical imaging applications to evaluate possible diseases in patients. But mostly medical images contain noise and low contrast and a lot of methods are being proposed to solve specific problems. Then, our study is based on the application of normalized cuts, a general segmentation algorithm, for MRI images. This method is robust to noise and initialization and it has also been used for medical segmentation giving promising results. We describe the method and combine it with the nystrm approximation to reduce the computational cost. Some results are shown.