venus-integration

Code to process data for integrating acquisition planning with VENUS

How?

Step 1. Set up your directory structure

input/
	2022-11-16-Scene.mrml
	input-pointNormal-Plane-markup.json
	input-anatomical-image.nii.gz (e.g. t2.nii.gz)
output/
preprocessing.sh
slice_select.py
write_slicer_markup_json.py

Step 2. Preprocessing your data

Label the spinal cord, vertebrae and vertebral boundaries within which you want to compute your slices.
Usage: ./preprocessing.sh anatomical_image.nii.gz contrast upper_vertebra lower_vertebra
Labels (integer values) corresponding to each vertebra and disc can be found here.

./preprocessing.sh t2.nii.gz t2 2 5 # 2 = mid C2; 5 = mid C5

Step 3. Slice selection and orthogonal plane generation

Find the indices of N slices (N = 5 in this example) that are equidistant along the centerline.
At each slice, compute a plane that is orthogonal to the centerline.

python slice_select.py t2.nii.gz t2_seg.nii.gz t2_boundary.nii.gz t2 5

Input

• input/t2.nii.gz was downloaded from the SCT t2 single subject tutorial.
• input/2022-11-16-Scene.mrml: necessary to generate the planes as a markup file that can be read by slicer.
• input/input-pointNormal-Plane-markup.json: necessary to generate the planes as a markup file that can be read by slicer.