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We have developed a novel method to describe human white matter anatomy usingan approach that is both intuitive and simple to use, and which automaticallyextracts white matter tracts from diffusion MRI volumes. Further, our methodsimplifies the quantification and statistical analysis of white matter tractson large diffusion MRI databases. This work reflects the careful syntacticaldefinition of major white matter fiber tracts in the human brain based on aneuroanatomist's expert knowledge. The framework is based on a novel querylanguage with a near-to-English textual syntax. This query language makes itpossible to construct a dictionary of anatomical definitions that describewhite matter tracts. The definitions include adjacent gray and white matterregions, and rules for spatial relations. This novel method makes it possibleto automatically label white matter anatomy across subjects. After describingthis method, we provide an example of its implementation where we encodeanatomical knowledge in human white matter for 10 association and 15 projectiontracts per hemisphere, along with 7 commissural tracts. Importantly, this novelmethod is comparable in accuracy to manual labeling. Finally, we presentresults applying this method to create a white matter atlas from 77 healthysubjects, and we use this atlas in a small proof-of-concept study to detectchanges in association tracts that characterize schizophrenia.

The White Matter Query Language: A Novel Approach for Describing Human White Matter Anatomy