Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas

• Published in: IEEE transactions on medical imaging Vol. 26; no. 11; pp. 1562 - 1575
• Main Authors: O'Donnell, Lauren J., Westin, Carl-Fredrik
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2007; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anatomy; Artificial Intelligence; Biomedical imaging; Brain; clustering; Computer Simulation; Corona; Corpus Callosum - anatomy & histology; diffusion magnetic resonance imaging (MRI); Diffusion Magnetic Resonance Imaging - methods; Diffusion tensor imaging; Hospitals; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image segmentation; Imaging, Three-Dimensional - methods; Magnetic resonance imaging; Models, Anatomic; Models, Neurological; Nerve fibers; Nerve Fibers, Myelinated - ultrastructure; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Stability; Subtraction Technique; Tensile stress; tractography; white matter; diffusion MRI; white matter; tractography; clustering; atlas
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2007.906785

We propose a new white matter atlas creation method that learns a model of the common white matter structures present in a group of subjects. We demonstrate that our atlas creation method, which is based on group spectral clustering of tractography, discovers structures corresponding to expected white matter anatomy such as the corpus callosum, uncinate fasciculus, cingulum bundles, arcuate fasciculus, and corona radiata. The white matter clusters are augmented with expert anatomical labels and stored in a new type of atlas that we call a high-dimensional white matter atlas. We then show how to perform automatic segmentation of tractography from novel subjects by extending the spectral clustering solution, stored in the atlas, using the Nystrom method. We present results regarding the stability of our method and parameter choices. Finally we give results from an atlas creation and automatic segmentation experiment. We demonstrate that our automatic tractography segmentation identifies corresponding white matter regions across hemispheres and across subjects, enabling group comparison of white matter anatomy.