  We have developed a novel method to describe human white matter anatomy using
an approach that is both intuitive and simple to use, and which automatically
extracts white matter tracts from diffusion MRI volumes. Further, our method
simplifies the quantification and statistical analysis of white matter tracts
on large diffusion MRI databases. This work reflects the careful syntactical
definition of major white matter fiber tracts in the human brain based on a
neuroanatomist's expert knowledge. The framework is based on a novel query
language with a near-to-English textual syntax. This query language makes it
possible to construct a dictionary of anatomical definitions that describe
white matter tracts. The definitions include adjacent gray and white matter
regions, and rules for spatial relations. This novel method makes it possible
to automatically label white matter anatomy across subjects. After describing
this method, we provide an example of its implementation where we encode
anatomical knowledge in human white matter for 10 association and 15 projection
tracts per hemisphere, along with 7 commissural tracts. Importantly, this novel
method is comparable in accuracy to manual labeling. Finally, we present
results applying this method to create a white matter atlas from 77 healthy
subjects, and we use this atlas in a small proof-of-concept study to detect
changes in association tracts that characterize schizophrenia.
