On describing human white matter anatomy: the white matter query language

Med Image Comput Comput Assist Interv. 2013;16(Pt 1):647-54. doi: 10.1007/978-3-642-40811-3_81.

Abstract

The main contribution of this work is the careful syntactical definition of major white matter tracts in the human brain based on a neuroanatomist's expert knowledge. We present a technique to formally describe white matter tracts and to automatically extract them from diffusion MRI data. The framework is based on a novel query language with a near-to-English textual syntax. This query language allows us to construct a dictionary of anatomical definitions describing white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This enables automated coherent labeling of white matter anatomy across subjects. We use our method to encode anatomical knowledge in human white matter describing 10 association and 8 projection tracts per hemisphere and 7 commissural tracts. The technique is shown to be comparable in accuracy to manual labeling. We present results applying this framework to create a white matter atlas from 77 healthy subjects, and we use this atlas in a proof-of-concept study to detect tract changes specific to schizophrenia.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence
  • Brain / cytology*
  • Diffusion Tensor Imaging / methods*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods
  • Information Storage and Retrieval / methods
  • Models, Anatomic*
  • Models, Neurological
  • Natural Language Processing*
  • Nerve Fibers, Myelinated / ultrastructure*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • User-Computer Interface*