TPTBox

The Torso Processing Toolbox (TPTBox) is a multi-functional Python package for processing BIDS-compliant medical imaging datasets (CT, MRI, and more).

Overview

TPTBox provides a unified interface for the most common tasks in medical image processing research:

• BIDS dataset navigation — load, filter, and iterate over BIDS-compliant datasets
• NIfTI I/O — read and write NIfTI files with consistent reorientation and resampling
• Points of Interest (POI) — compute and manipulate anatomical landmarks on vertebrae
• 2D snapshots — modular, multi-view MIP and overlay image generation
• 3D mesh generation — surface meshes from segmentations with configurable rendering
• Registration — rigid (point- and intensity-based) and deformable registration via ANTs and DeepALI
• Segmentation — integration with SPINEPS and nnU-Net inference pipelines
• Image stitching — multi-station field-of-view stitching
• Logging — structured, consistent logging across long-running pipelines

Quick Example

from TPTBox import NII, BIDS_Global_info

# Load a NIfTI and reorient + resample
nii = NII.load("path/to/image.nii.gz", seg=False)
nii_ras = nii.reorient(("R", "A", "S"))
nii_1mm = nii_ras.rescale((1.0, 1.0, 1.0))

# Iterate over a BIDS dataset
bids = BIDS_Global_info(["path/to/dataset"], parents=["rawdata"])
for subject, container in bids.enumerate_subjects():
    t2w = container.new_query().filter("format", "T2w").first()
    if t2w is not None:
        nii = t2w.open_nii()

See Getting Started for installation instructions and more examples.