tractoptions

Tractoptions is a configuration construct used in tractography software to specify parameters controlling the generation of neural fiber tracts. It is typically implemented as a data structure or a small class/object that can be serialized to disk and passed between pipeline stages. The term is used across several neuroimaging toolkits, though exact field names may vary.

Common fields may include seed_count or seed_density, step_size, max_angle or max_curvature, min_length, max_length, termination_mask or termination_criteria, model or distribution (e.g., deterministic or probabilistic), method (e.g., streamline, probabilistic tracking), angular_threshold, fiber_model (tensor, Q-ball, etc.), and integration_method (e.g., Euler, Runge-Kutta). Some implementations also include pre-processing flags like resample seeds, mask, or weighting.

Usage: A user constructs a tractoptions instance with desired parameters, passes it to the tractography engine, which then generates a tractogram. The object may be saved as JSON or YAML, enabling reproducibility. Tools may override certain fields via configuration files or command-line arguments, allowing flexible experimentation.

Relation and interpretation: tractoptions complement input data such as diffusion-weighted images and models. They do not perform processing themselves but govern the algorithms used during tract generation. Proper choice of options impacts tractography outcomes, including sensitivity to crossing fibers and susceptibility to false positives.

See also: tractography, diffusion MRI, tractogram, deterministic tracking, probabilistic tracking, diffusion models.