Title :
A comprehensive riemannian framework for the analysis of white matter fiber tracts
Author :
Mani, Meena ; Kurtek, Sebastian ; Barillot, Christian ; Srivastava, Anuj
Author_Institution :
Visages Project, IRISA/INRIA Rennes, Rennes, France
Abstract :
A quantitative analysis of white matter fibers is based on different physical features (shape, scale, orientation and position) of the fibers, depending on the specific application. Due to the different properties of these features, one usually designs different metrics and spaces to treat them individually. We propose a comprehensive Riemannian framework that allows for a joint analysis of these features in a consistent manner. For each feature combination, we provide a formula for the distance, i.e. quantification of differences between fibers and a formula for geodesics, i.e. optimal deformations of fibers into each other. We illustrate this framework in the context of clustering fiber tracts from the corpus callosum and study the results from different combinations of features.
Keywords :
biomedical MRI; image reconstruction; image segmentation; medical image processing; neurophysiology; pattern clustering; clustering fiber tracts; comprehensive Riemannian framework; corpus callosum; feature combination; fiber deformations; geodesics; white matter fiber tracts; Diffusion tensor imaging; Diseases; Extraterrestrial measurements; Information analysis; Labeling; Magnetic resonance imaging; Neurosurgery; Shape; Statistical analysis; Tensile stress; DTI fiber clustering; Riemannian shape analysis; elastic shape metric; joint feature spaces;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2010.5490185