Table 1 Sampling of ANTsX functionality

From: The ANTsX ecosystem for mapping the mouse brain

ANTsPy: Preprocessing

bias field correction

n4_bias_field_correction(...)

image denoising

denoise_image(...)

ANTsPy: Registration

intensity image registration

registration(...)

label image registration

label_image_registration(...)

image transformation

apply_transforms(...)

template generation

build_template(...)

landmark registration

fit_transform_to_paired_points(...)

time-varying landmark reg.

fit_time_varying_transform_to_point_sets(...)

integrate velocity field

integrate_velocity_field(...)

invert displacement field

invert_displacement_field(...)

ANTsPy: Segmentation

MRF-based segmentation

atropos(...)

Joint label fusion

joint_label_fusion(...)

diffeomorphic thickness

kelly_kapowski(...)

ANTsPy: Miscellaneous

Regional intensity statistics

label_stats(...)

Regional shape measures

label_geometry_measures(...)

B-spline approximation

fit_bspline_object_to_scattered_data(...)

Visualize images and overlays

plot(...)

ANTsPyNet: Mouse-specific

brain extraction

mouse_brain_extraction(...modality="t2"...)

brain parcellation

mouse_brain_parcellation(...)

cortical thickness

mouse_cortical_thickness(...)

super resolution

mouse_histology_super_resolution(...)

  1. ANTsX provides state-of-the-art functionality for processing biomedical image data. Such tools, including deep learning networks, support a variety of mapping-related tasks. A more comprehensive listing of ANTsX tools with self-contained R and Python examples is provided as a gist page on GitHub (https://tinyurl.com/antsxtutorial).