Analysis of ventricles in alzheimer MR images using coherence enhancing diffusion filter and level set method

Alzheimer's disease is a fatal neurodegenerative disorder that causes enlargement of ventricles and shrinkage of whole brain leading to slow progression of dementia. Ventricle enlargement is an important structural biomarker for the diagnosis of AD. Magnetic resonance imaging is a useful non invasive tool which depicts the pathology of brain structures and improves the diagnosis of AD. In this work, an attempt has been made to segment ventricles from both normal and AD MR images using modified distance regularized level set method. The image gradient of coherence enhanced diffusion filtered image is used as an edge map for level set evolution. Geometric features are extracted from the segmented ventricle to identify its clinical significance in the AD diagnosis. Results show that, the proposed method of integration of non linear diffusion filter with level set method is able to segment the ventricles in both normal and AD images. The extracted shape based features are able to differentiate the AD subjects from normals with high statistical significance (p<;0.0001). Thus this study seems to be clinically useful.