Build a patient vasculature digital twin from CT (preprocess + segment). Use when asked to preprocess CT, segment vessels, extract centerline, or prepare ct_cache for viewport/DRR.
npx skills add https://github.com/NVIDIA/skills --skill i4h-catheter-navigation-digital-twin
Download or locate a CT volume, preprocess it to an attenuation cache, and segment the arterial tree into vessel mask + centerline - the vasculature digital twin required for patient-specific viewport and DRR runs.
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/catheter_navigation" ]; then
ROOT="${I4H_WORKFLOWS:-$HOME/i4h-workflows}"
[ -d "$ROOT/workflows/catheter_navigation" ] || git clone https://github.com/isaac-for-healthcare/i4h-workflows "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"; cd "$ROOT"
--output-dir / --ct-dir (e.g. /tmp/ct_cache) holds mu_volume.npy, metadata.json, and after segmentation vessel mask + centerline artifacts.Run the steps below in order. Each step is a separate bash call; variables persist in the local agent's tmux session.
REPO_ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"; [ -d "$REPO_ROOT/workflows/catheter_navigation" ] || REPO_ROOT="$HOME/i4h-workflows"
WF_ROOT="${REPO_ROOT}/workflows/catheter_navigation"
RUN_DIR="${WF_ROOT}/runs/digital_twin_$(date +%Y%m%d_%H%M%S)"
mkdir -p "${RUN_DIR}/logs"
ln -sfn "${RUN_DIR}" "${WF_ROOT}/runs/.latest"
# User-supplied or downloaded subject directory (must contain ct.nii.gz + segmentations/)
SUBJ="${SUBJ:-}"
CACHE="${CACHE:-/tmp/ct_cache}"
if [ -z "${SUBJ}" ] || [ ! -f "${SUBJ}/ct.nii.gz" ]; then
echo "digital-twin: set SUBJ to an extracted TotalSegmentator subject (got '${SUBJ:-<unset>}')." >&2
echo "Example: SUBJ=/path/to/Totalsegmentator_dataset_small_v201/s0011" >&2
exit 1
fi
Only run when the user has no CT data yet.
curl -L "https://www.dropbox.com/scl/fi/pee5yxebfxrhz007cbuy5/Totalsegmentator_dataset_small_v201.zip?rlkey=osvfk02jc4lw5gr6uhrldtb9e&dl=1" \
-o "${RUN_DIR}/Totalsegmentator_dataset_small_v201.zip"
unzip "${RUN_DIR}/Totalsegmentator_dataset_small_v201.zip" -d "${RUN_DIR}/Totalsegmentator_dataset_small_v201"
ls "${RUN_DIR}/Totalsegmentator_dataset_small_v201"
# Then set SUBJ to one extracted subject before continuing.
"${REPO_ROOT}/i4h" run catheter_navigation preprocess_ct --local \
--run-args="--nifti ${SUBJ}/ct.nii.gz --output-dir ${CACHE} --save-hu" \
2>&1 | tee "${RUN_DIR}/logs/preprocess_ct.log"
"${REPO_ROOT}/i4h" run catheter_navigation segment_vessels --local \
--run-args="--ct-dir ${CACHE} --ts-gt-dir ${SUBJ}/segmentations" \
2>&1 | tee "${RUN_DIR}/logs/segment_vessels.log"
test -f "${CACHE}/mu_volume.npy"
test -f "${CACHE}/metadata.json"
ls -la "${CACHE}"
SUBJ must point at one extracted subject with ct.nii.gz and segmentations/ (TotalSegmentator layout).CACHE is reused by [[i4h-catheter-navigation-viewport]] and cache-based [[i4h-catheter-navigation-render-drr]].SUBJ unset or missing ct.nii.gz - Fix: download Step 2 dataset or set SUBJ to an existing subject path.--ts-gt-dir - Fix: confirm ${SUBJ}/segmentations exists (TotalSegmentator ground truth).Report CACHE path, key artifacts present, log paths under RUN_DIR, and recommend [[i4h-catheter-navigation-viewport]] or [[i4h-catheter-navigation-render-drr]] next.
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Take nvidia/i4h-catheter-navigation-digital-twin from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.