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

arXiv: https://arxiv.org/abs/1512.07404 · HTML: https://mlsanity.com/paper/1512.07404/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Dec 2015.

## Built on by (most cited first, 13 of 13)

- [Diffusion MRI with Machine Learning](https://mlsanity.com/paper/2402.00019/) (2024)
- [Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods](https://mlsanity.com/paper/2306.05623/) (2023)
- [FIESTA: Autoencoders for accurate fiber segmentation in tractography](https://mlsanity.com/paper/2212.00143/) (2022)
- [Detailed delineation of the fetal brain in diffusion MRI via multi-task learning](https://mlsanity.com/paper/2409.06716/) (2024)
- [Anatomically Constrained Tractography of the Fetal Brain](https://mlsanity.com/paper/2403.02444/) (2024)
- [Assessing Streamline Plausibility Through Randomized Iterative Spherical-Deconvolution Informed Tractogram Filtering](https://mlsanity.com/paper/2205.04843/) (2022)
- [Streamline tractography of the fetal brain in utero with machine learning](https://mlsanity.com/paper/2408.14326/) (2024)
- [First Order Logic with Fuzzy Semantics for Describing and Recognizing Nerves in Medical Images](https://mlsanity.com/paper/2505.00173/) (2025)
- [Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering](https://mlsanity.com/paper/2307.05786/) (2023)
- [DDEvENet: Evidence-based Ensemble Learning for Uncertainty-aware Brain Parcellation Using Diffusion MRI](https://mlsanity.com/paper/2409.07020/) (2024)
- [FetDTIAlign: A Deep Learning Framework for Affine and Deformable Registration of Fetal Brain dMRI](https://mlsanity.com/paper/2502.01057/) (2025)
- [Global Context Is All You Need for Parallel Efficient Tractography Parcellation](https://mlsanity.com/paper/2503.07104/) (2025)
- [Visionerves: Automatic and Reproducible Hybrid AI for Peripheral Nervous System Recognition Applied to Endometriosis Cases](https://mlsanity.com/paper/2509.18185/) (2025)

## Abstract (arXiv)

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.